173 KiB
173 KiB
| 1 | title | authors | year | venue | publisher | citation_count | avg_citations_per_year |
|---|---|---|---|---|---|---|---|
| 2 | Human-in-the-loop machine learning: a state of the art | E Mosqueira | 2023 | Artificial Intelligence … | Springer | 865 | 288.3333333333333 |
| 3 | Machine learning for battery systems applications: Progress, challenges, and opportunities | Z Nozarijouybari, HK Fathy | 2024 | Journal of Power Sources | Elsevier | 77 | 38.5 |
| 4 | Machine learning for nanoplasmonics | JF Masson, JS Biggins, E Ringe | 2023 | Nature Nanotechnology | nature.com | 106 | 35.333333333333336 |
| 5 | Machine learning operations (mlops): Overview, definition, and architecture | D Kreuzberger, N Kühl, S Hirschl | 2023 | IEEE access | ieeexplore.ieee.org | 775 | 258.3333333333333 |
| 6 | Agricultural databases evaluation with machine learning procedure | M Amini, A Rahmani | 2023 | … Journal of Engineering and Applied Science | papers.ssrn.com | 158 | 52.666666666666664 |
| 7 | Small data machine learning in materials science | P Xu, X Ji, M Li, W Lu | 2023 | npj Computational Materials | nature.com | 459 | 153.0 |
| 8 | [PDF][PDF] Machine learning in cybersecurity: Techniques and challenges | J Bharadiya | 2023 | European Journal of Technology | academia.edu | 164 | 54.666666666666664 |
| 9 | [BOOK][B] Mathematical analysis of machine learning algorithms | T Zhang | 2023 | 2023 | books.google.com | 104 | 34.666666666666664 |
| 10 | Pushing the frontiers in climate modelling and analysis with machine learning | V Eyring, WD Collins, P Gentine, EA Barnes… | 2024 | Nature Climate … | nature.com | 121 | 60.5 |
| 11 | of Machine Learning Techniques | V Sutaria, A Jain | 2025 | Intelligent Strategies for ICT: Proceedings of … | books.google.com | 188 | 188.0 |
| 12 | [HTML][HTML] Machine learning applications in agriculture: current trends, challenges, and future perspectives | SO Araujo, RS Peres, JC Ramalho, F Lidon, J Barata | 2023 | Agronomy | mdpi.com | 179 | 59.666666666666664 |
| 13 | Machine learning in environmental research: common pitfalls and best practices | JJ Zhu, M Yang, ZJ Ren | 2023 | Environmental Science & Technology | ACS Publications | 386 | 128.66666666666666 |
| 14 | OpenMM 8: molecular dynamics simulation with machine learning potentials | P Eastman, R Galvelis, RP Peláez… | 2023 | The Journal of … | ACS Publications | 274 | 91.33333333333333 |
| 15 | Research on machine learning with algorithms and development | L Yu, X Zhao, J Huang, H Hu… | 2023 | Journal of Theory and … | centuryscipub.com | 43 | 14.333333333333334 |
| 16 | Machine learning for a sustainable energy future | Z Yao, Y Lum, A Johnston, LM Mejia | 2023 | Nature Reviews … | nature.com | 393 | 131.0 |
| 17 | A systematic review of teaching and learning machine learning in K-12 education | IT Sanusi, SS Oyelere, H Vartiainen, J Suhonen… | 2023 | Education and … | Springer | 229 | 76.33333333333333 |
| 18 | Crop prediction model using machine learning algorithms | E Elbasi, C Zaki, AE Topcu, W Abdelbaki, AI Zreikat… | 2023 | Applied Sciences | mdpi.com | 268 | 89.33333333333333 |
| 19 | Machine learning in architecture | B Topuz, NÇ Alp | 2023 | Automation in Construction | Elsevier | 53 | 17.666666666666668 |
| 20 | AI and machine learning for real-world problems | H Nozari, J Ghahremani | 2024 | Advances in computers | Elsevier | 107 | 53.5 |
| 21 | [PDF][PDF] An unsupervised machine learning algorithms: Comprehensive review | S Naeem, A Ali, S Anam… | 2023 | International Journal of … | researchgate.net | 264 | 88.0 |
| 22 | eXtreme gradient boosting algorithm with machine learning: A review | ZA Ali, ZH Abduljabbar, HA Tahir, AB Sallow… | 2023 | Academic Journal of … | cir.nii.ac.jp | 197 | 65.66666666666667 |
| 23 | A review of evaluation metrics in machine learning algorithms | G Naidu, T Zuva, EM Sibanda | 2023 | line conference | Springer | 447 | 149.0 |
| 24 | A review of machine learning algorithms for biomedical applications | VA Binson, S Thomas, M Subramoniam, J Arun… | 2024 | Annals of Biomedical … | Springer | 81 | 40.5 |
| 25 | [HTML][HTML] Understanding of machine learning with deep learning: architectures, workflow, applications and future directions | MM Taye | 2023 | Computers | mdpi.com | 1000 | 333.3333333333333 |
| 26 | Machine learning methods for small data challenges in molecular science | B Dou, Z Zhu, E Merkurjev, L Ke, L Chen… | 2023 | Chemical … | ACS Publications | 343 | 114.33333333333333 |
| 27 | Security Threats and Detection Mechanisms in Machine Learning | K Madhuri | 2023 | Handbook of Artificial Intelligence | books.google.com | 165 | 55.0 |
| 28 | [HTML][HTML] The challenges of machine learning: A critical review | E Barbierato, A Gatti | 2024 | Electronics | mdpi.com | 138 | 69.0 |
| 29 | An overview of machine learning classification techniques | AFAH Alnuaimi, THK Albaldawi | 2024 | bio | conferences.org | 82 | 41.0 |
| 30 | [HTML][HTML] Advancements and challenges in machine learning: A comprehensive review of models, libraries, applications, and algorithms | S Tufail, H Riggs, M Tariq, AI Sarwat | 2023 | Electronics | mdpi.com | 215 | 71.66666666666667 |
| 31 | Predictive models for concrete properties using machine learning and deep learning approaches: A review | MM Moein, A Saradar, K Rahmati… | 2023 | Journal of Building … | Elsevier | 395 | 131.66666666666666 |
| 32 | [HTML][HTML] Supervised machine learning in drug discovery and development: Algorithms, applications, challenges, and prospects | G Obaido, ID Mienye, OF Egbelowo… | 2024 | Machine Learning with … | Elsevier | 74 | 37.0 |
| 33 | Promising directions of machine learning for partial differential equations | SL Brunton, JN Kutz | 2024 | Nature Computational Science | nature.com | 108 | 54.0 |
| 34 | Unsupervised machine learning methods and emerging applications in healthcare | CM Eckhardt, SJ Madjarova, RJ Williams… | 2023 | Knee Surgery | Springer | 161 | 53.666666666666664 |
| 35 | Impact of machine learning on management, healthcare and agriculture | H Pallathadka, M Mustafa, DT Sanchez… | 2023 | Materials Today … | Elsevier | 248 | 82.66666666666667 |
| 36 | [HTML][HTML] Enhanced sampling with machine learning | S Mehdi, Z Smith, L Herron, Z Zou… | 2024 | Annual Review of … | annualreviews.org | 89 | 44.5 |
| 37 | Machine learning for the physics of climate | A Bracco, J Brajard, HA Dijkstra… | 2025 | Nature Reviews … | nature.com | 48 | 48.0 |
| 38 | Evaluation metrics and statistical tests for machine learning | O Rainio, J Teuho, R Klén | 2024 | Scientific Reports | nature.com | 810 | 405.0 |
| 39 | [BOOK][B] Ensemble methods for machine learning | G Kunapuli | 2023 | 2023 | books.google.com | 152 | 50.666666666666664 |
| 40 | Evaluating machine learning models and their diagnostic value | G Varoquaux, O Colliot | 2023 | Machine learning for brain disorders | Springer | 215 | 71.66666666666667 |
| 41 | Interpretable machine learning for science with PySR and SymbolicRegression. jl | M Cranmer | 2023 | arXiv preprint arXiv:2305.01582 | arxiv.org | 475 | 158.33333333333334 |
| 42 | The role of artificial neural network and machine learning in utilizing spatial information | A Goel, AK Goel, A Kumar | 2023 | Spatial Information Research | Springer | 249 | 83.0 |
| 43 | Traffic management approaches using machine learning and deep learning techniques: A survey | H Almukhalfi, A Noor, TH Noor | 2024 | Engineering Applications of Artificial … | Elsevier | 106 | 53.0 |
| 44 | Evaluation of a decided sample size in machine learning applications | D Rajput, WJ Wang, CC Chen | 2023 | BMC bioinformatics | Springer | 334 | 111.33333333333333 |
| 45 | Byzantine machine learning: A primer | R Guerraoui, N Gupta, R Pinot | 2024 | ACM Computing Surveys | dl.acm.org | 55 | 27.5 |
| 46 | Future of machine learning in geotechnics | KK Phoon, W Zhang | 2023 | … : Assessment and Management of Risk for … | Taylor & Francis | 262 | 87.33333333333333 |
| 47 | Representations of materials for machine learning | J Damewood, J Karaguesian, JR Lunger… | 2023 | Annual Review of … | annualreviews.org | 103 | 34.333333333333336 |
| 48 | [HTML][HTML] Probabilistic weather forecasting with machine learning | I Price, A Sanchez | 2025 | Nature | nature.com | 267 | 267.0 |
| 49 | Revolutionizing drug formulation development: The increasing impact of machine learning | Z Bao, J Bufton, RJ Hickman, A Aspuru | 2023 | Advanced Drug Delivery … | Elsevier | 67 | 22.333333333333332 |
| 50 | [HTML][HTML] Knowledge Discovery: Methods from data mining and machine learning | X Shu, Y Ye | 2023 | Social Science Research | Elsevier | 280 | 93.33333333333333 |
| 51 | [HTML][HTML] Ethical and bias considerations in artificial intelligence/machine learning | MG Hanna, L Pantanowitz, B Jackson, O Palmer… | 2025 | Modern Pathology | Elsevier | 207 | 207.0 |
| 52 | Position: Why we must rethink empirical research in machine learning | M Herrmann, FJD Lange, K Eggensperger… | 2024 | arXiv preprint arXiv … | arxiv.org | 35 | 17.5 |
| 53 | [HTML][HTML] Machine learning and remote sensing integration for leveraging urban sustainability: A review and framework | F Li, T Yigitcanlar, M Nepal, K Nguyen, F Dur | 2023 | Sustainable Cities and … | Elsevier | 184 | 61.333333333333336 |
| 54 | A review of machine learning for modeling air quality: Overlooked but important issues | D Tang, Y Zhan, F Yang | 2024 | Atmospheric Research | Elsevier | 62 | 31.0 |
| 55 | [HTML][HTML] Exploring the impact of ChatGPT on education: A web mining and machine learning approach | A Rejeb, K Rejeb, A Appolloni, H Treiblmaier… | 2024 | … International Journal of … | Elsevier | 160 | 80.0 |
| 56 | [HTML][HTML] Artificial intelligence, machine learning and deep learning in advanced robotics, a review | M Soori, B Arezoo, R Dastres | 2023 | Cognitive Robotics | Elsevier | 1221 | 407.0 |
| 57 | Machine learning in agriculture: a review of crop management applications | I Attri, LK Awasthi, TP Sharma | 2024 | Multimedia Tools and Applications | Springer | 127 | 63.5 |
| 58 | [HTML][HTML] Machine learning methods in weather and climate applications: A survey | L Chen, B Han, X Wang, J Zhao, W Yang, Z Yang | 2023 | Applied Sciences | mdpi.com | 183 | 61.0 |
| 59 | Advances in machine learning for wearable sensors | X Xiao, J Yin, J Xu, T Tat, J Chen | 2024 | ACS nano | ACS Publications | 50 | 25.0 |
| 60 | Mlagentbench: Evaluating language agents on machine learning experimentation | Q Huang, J Vora, P Liang, J Leskovec | 2023 | arXiv preprint arXiv:2310.03302 | arxiv.org | 140 | 46.666666666666664 |
| 61 | Machine learning in marketing: Recent progress and future research directions | D Herhausen, SF Bernritter, EWT Ngai, A Kumar… | 2024 | Journal of Business … | Elsevier | 66 | 33.0 |
| 62 | Autoencoders and their applications in machine learning: a survey | K Berahmand, F Daneshfar, ES Salehi, Y Li… | 2024 | Artificial intelligence … | Springer | 413 | 206.5 |
| 63 | In-network machine learning using programmable network devices: A survey | C Zheng, X Hong, D Ding, S Vargaftik… | 2023 | … Surveys & Tutorials | ieeexplore.ieee.org | 65 | 21.666666666666668 |
| 64 | Opportunities and challenges for machine learning-assisted enzyme engineering | J Yang, FZ Li, FH Arnold | 2024 | ACS Central Science | ACS Publications | 139 | 69.5 |
| 65 | Tiny machine learning: Progress and futures [feature] | J Lin, L Zhu, WM Chen, WC Wang… | 2023 | IEEE Circuits and … | ieeexplore.ieee.org | 141 | 47.0 |
| 66 | Artificial intelligence and machine learning in clinical medicine, 2023 | CJ Haug, JM Drazen | 2023 | New England Journal of Medicine | Mass Medical Soc | 1040 | 346.6666666666667 |
| 67 | A survey of machine learning and deep learning in remote sensing of geological environment: Challenges, advances, and opportunities | W Han, X Zhang, Y Wang, L Wang, X Huang… | 2023 | ISPRS Journal of … | Elsevier | 242 | 80.66666666666667 |
| 68 | Machine learning-aided generative molecular design | Y Du, AR Jamasb, J Guo, T Fu, C Harris… | 2024 | Nature Machine … | nature.com | 138 | 69.0 |
| 69 | Emerging trends in machine learning: a polymer perspective | TB Martin, DJ Audus | 2023 | ACS Polymers Au | ACS Publications | 131 | 43.666666666666664 |
| 70 | [HTML][HTML] Machine learning: Models, challenges, and research directions | T Talaei Khoei, N Kaabouch | 2023 | Future Internet | mdpi.com | 59 | 19.666666666666668 |
| 71 | Machine learning in oil and gas exploration: A review | A Lawal, Y Yang, H He, NL Baisa | 2024 | Ieee Access | ieeexplore.ieee.org | 49 | 24.5 |
| 72 | Machine learning and the five big ideas in AI | D Touretzky, C Gardner | 2023 | International journal of … | Springer | 179 | 59.666666666666664 |
| 73 | Foundations & trends in multimodal machine learning: Principles, challenges, and open questions | PP Liang, A Zadeh, LP Morency | 2024 | ACM Computing Surveys | dl.acm.org | 287 | 143.5 |
| 74 | Ensemble deep learning and machine learning: applications, opportunities, challenges, and future directions | N Rane, SP Choudhary, J Rane | 2024 | Studies in Medical and Health … | sabapub.com | 102 | 51.0 |
| 75 | What is machine learning, artificial neural networks and deep learning?—Examples of practical applications in medicine | J Kufel, K Bargieł | 2023 | Diagnostics | mdpi.com | 295 | 98.33333333333333 |
| 76 | [HTML][HTML] Artificial intelligence and machine learning in energy systems: A bibliographic perspective | A Entezari, A Aslani, R Zahedi, Y Noorollahi | 2023 | Energy Strategy Reviews | Elsevier | 344 | 114.66666666666667 |
| 77 | [HTML][HTML] A review of machine learning and deep learning approaches on mental health diagnosis | NK Iyortsuun, SH Kim, M Jhon, HJ Yang, S Pant | 2023 | Healthcare | mdpi.com | 242 | 80.66666666666667 |
| 78 | [HTML][HTML] A brief survey of machine learning and deep learning techniques for e-commerce research | X Zhang, F Guo, T Chen, L Pan, G Beliakov… | 2023 | Journal of Theoretical … | mdpi.com | 103 | 34.333333333333336 |
| 79 | Advances of machine learning in materials science: Ideas and techniques | SS Chong, YS Ng, HQ Wang, JC Zheng | 2024 | Frontiers of Physics | Springer | 74 | 37.0 |
| 80 | Machine learning: Review and trends | MOK Mendonça, SL Netto, PSR Diniz… | 2024 | … and machine learning … | Elsevier | 41 | 20.5 |
| 81 | Causal machine learning for predicting treatment outcomes | S Feuerriegel, D Frauen, V Melnychuk, J Schweisthal… | 2024 | Nature Medicine | nature.com | 240 | 120.0 |
| 82 | Cardiovascular diseases prediction by machine learning incorporation with deep learning | S Subramani, N Varshney, MV Anand… | 2023 | Frontiers in … | frontiersin.org | 111 | 37.0 |
| 83 | Machine learning for synthetic data generation: a review | Y Lu, M Shen, H Wang, X Wang, C van Rechem… | 2023 | arXiv preprint arXiv … | arxiv.org | 326 | 108.66666666666667 |
| 84 | Machine learning political orders | L Amoore | 2023 | Review of International Studies | cambridge.org | 115 | 38.333333333333336 |
| 85 | Mle-bench: Evaluating machine learning agents on machine learning engineering | JS Chan, N Chowdhury, O Jaffe, J Aung… | 2024 | arXiv preprint arXiv … | arxiv.org | 104 | 52.0 |
| 86 | Machine learning in earthquake seismology | SM Mousavi, GC Beroza | 2023 | Annual Review of Earth and … | annualreviews.org | 227 | 75.66666666666667 |
| 87 | Machine learning process evaluating damage classification of composites | M Amini, A Rahmani | 2023 | International Journal of Science and … | papers.ssrn.com | 148 | 49.333333333333336 |
| 88 | [HTML][HTML] Artificial intelligence, machine learning, and deep learning in liver transplantation | M Bhat, M Rabindranath, BS Chara, DA Simonetto | 2023 | Journal of hepatology | Elsevier | 170 | 56.666666666666664 |
| 89 | Machine learning applications in stroke medicine: advancements, challenges, and future prospectives | M Daidone, S Ferrantelli… | 2024 | Neural regeneration … | journals.lww.com | 98 | 49.0 |
| 90 | Findings on teaching machine learning in high school: A ten-year systematic literature review | RM Martins, C Gresse Von Wangenheim | 2023 | Informatics in Education | ceeol.com | 321 | 107.0 |
| 91 | [HTML][HTML] Systematic literature review: Quantum machine learning and its applications | D Peral | 2024 | Computer Science … | Elsevier | 279 | 139.5 |
| 92 | Coronavirus disease (COVID-19) cases analysis using machine-learning applications | AS Kwekha | 2023 | Applied nanoscience | Springer | 353 | 117.66666666666667 |
| 93 | Open-world machine learning: A review and new outlooks | F Zhu, S Ma, Z Cheng, XY Zhang, Z Zhang… | 2024 | arXiv e … | ui.adsabs.harvard.edu | 46 | 23.0 |
| 94 | [HTML][HTML] Machine learning for chemistry: basics and applications | YF Shi, ZX Yang, S Ma, PL Kang, C Shang, P Hu… | 2023 | Engineering | Elsevier | 67 | 22.333333333333332 |
| 95 | Machine learning in metaverse security: Current solutions and future challenges | Y Otoum, N Gottimukkala, N Kumar, A Nayak | 2024 | ACM Computing Surveys | dl.acm.org | 41 | 20.5 |
| 96 | [HTML][HTML] An overview of machine learning, deep learning, and reinforcement learning-based techniques in quantitative finance: recent progress and challenges | SK Sahu, A Mokhade, ND Bokde | 2023 | Applied Sciences | mdpi.com | 184 | 61.333333333333336 |
| 97 | On some limitations of current machine learning weather prediction models | M Bonavita | 2024 | Geophysical Research Letters | Wiley Online Library | 110 | 55.0 |
| 98 | An interactive teaching evaluation system for preschool education in universities based on machine learning algorithm | D Li | 2024 | Computers in human behavior | Elsevier | 62 | 31.0 |
| 99 | Machine learning for intelligent data analysis and automation in cybersecurity: current and future prospects | IH Sarker | 2023 | Annals of Data Science | Springer | 301 | 100.33333333333333 |
| 100 | Sensing and machine learning for automotive perception: A review | A Pandharipande, CH Cheng, J Dauwels… | 2023 | IEEE Sensors … | ieeexplore.ieee.org | 136 | 45.333333333333336 |
| 101 | Predicting agriculture yields based on machine learning using regression and deep learning | P Sharma, P Dadheech, N Aneja, S Aneja | 2023 | IEEE Access | ieeexplore.ieee.org | 110 | 36.666666666666664 |
| 102 | Machine Learning and Genetic Algorithms: A case study on image reconstruction | C Cavallaro, V Cutello, M Pavone, F Zito | 2024 | Based Systems | Elsevier | 52 | 26.0 |
| 103 | Accurately identifying hemagglutinin using sequence information and machine learning methods | X Zou, L Ren, P Cai, Y Zhang, H Ding, K Deng… | 2023 | Frontiers in … | frontiersin.org | 110 | 36.666666666666664 |
| 104 | [HTML][HTML] A brief review of machine learning algorithms in forest fires science | R Alkhatib, W Sahwan, A Alkhatieb, B Schütt | 2023 | Applied Sciences | mdpi.com | 115 | 38.333333333333336 |
| 105 | Machine learning solutions for the security of wireless sensor networks: A review | YY Ghadi, T Mazhar, T Al Shloul, T Shahzad… | 2024 | Ieee … | ieeexplore.ieee.org | 74 | 37.0 |
| 106 | [HTML][HTML] Machine learning and prediction of infectious diseases: a systematic review | OE Santangelo, V Gentile, S Pizzo, D Giordano… | 2023 | Machine Learning and … | mdpi.com | 124 | 41.333333333333336 |
| 107 | The role of machine learning in tribology: A systematic review | UMR Paturi, ST Palakurthy, NS Reddy | 2023 | Archives of Computational … | Springer | 102 | 34.0 |
| 108 | Feature selection techniques for machine learning: a survey of more than two decades of research | D Theng, KK Bhoyar | 2024 | Knowledge and Information Systems | Springer | 330 | 165.0 |
| 109 | Application of Machine Learning and Deep Learning in Finite Element Analysis: A Comprehensive Review. | D Nath, DR Neog, SS Gautam | 2024 | Archives of computational … | search.ebscohost.com | 83 | 41.5 |
| 110 | Recent progresses in machine learning assisted Raman spectroscopy | Y Qi, D Hu, Y Jiang, Z Wu, M Zheng… | 2023 | Advanced Optical … | Wiley Online Library | 181 | 60.333333333333336 |
| 111 | Machine learning for functional protein design | P Notin, N Rollins, Y Gal, C Sander, D Marks | 2024 | Nature biotechnology | nature.com | 207 | 103.5 |
| 112 | [HTML][HTML] Quantum machine learning: A review and case studies | A Zeguendry, Z Jarir, M Quafafou | 2023 | Entropy | mdpi.com | 204 | 68.0 |
| 113 | The impact of data normalization on the accuracy of machine learning algorithms: A comparative analysis | K Cabello | 2023 | … conference on soft … | Springer | 204 | 68.0 |
| 114 | Differentiable modelling to unify machine learning and physical models for geosciences | C Shen, AP Appling, P Gentine, T Bandai… | 2023 | Nature Reviews Earth & … | nature.com | 294 | 98.0 |
| 115 | Towards foundation models for scientific machine learning: Characterizing scaling and transfer behavior | S Subramanian, P Harrington… | 2023 | Advances in … | proceedings.neurips.cc | 130 | 43.333333333333336 |
| 116 | Fairness issues, current approaches, and challenges in machine learning models | TD Jui, P Rivas | 2024 | International Journal of Machine Learning and … | Springer | 63 | 31.5 |
| 117 | Early detection of Parkinson's disease using machine learning | A Govindu, S Palwe | 2023 | Procedia Computer Science | Elsevier | 214 | 71.33333333333333 |
| 118 | [HTML][HTML] From machine learning to deep learning: Advances of the recent data-driven paradigm shift in medicine and healthcare | C Chakraborty, M Bhattacharya, S Pal… | 2024 | Current Research in … | Elsevier | 194 | 97.0 |
| 119 | Knowledge-integrated machine learning for materials: lessons from gameplaying and robotics | K Hippalgaonkar, Q Li, X Wang, JW Fisher III… | 2023 | Nature Reviews … | nature.com | 126 | 42.0 |
| 120 | The well: a large-scale collection of diverse physics simulations for machine learning | R Ohana, M McCabe, L Meyer… | 2024 | Advances in … | proceedings.neurips.cc | 44 | 22.0 |
| 121 | The role of machine learning in cybersecurity | G Apruzzese, P Laskov, E Montes de Oca… | 2023 | … Threats: Research and … | dl.acm.org | 277 | 92.33333333333333 |
| 122 | Machine learning optimization techniques: a survey, classification, challenges, and future research issues | K Bian, R Priyadarshi | 2024 | Archives of Computational Methods in Engineering | Springer | 96 | 48.0 |
| 123 | [PDF][PDF] Navigating the future: integrating AI and machine learning in hr practices for a digital workforce | CG Okatta, FA Ajayi, O Olawale | 2024 | Computer science & IT research … | researchgate.net | 132 | 66.0 |
| 124 | Recent advances and application of machine learning in food flavor prediction and regulation | H Ji, D Pu, W Yan, Q Zhang, M Zuo, Y Zhang | 2023 | Trends in Food Science & … | Elsevier | 138 | 46.0 |
| 125 | When physics meets machine learning: A survey of physics-informed machine learning | C Meng, S Griesemer, D Cao, S Seo, Y Liu | 2025 | Machine Learning for … | Springer | 164 | 164.0 |
| 126 | Open-world machine learning: applications, challenges, and opportunities | J Parmar, S Chouhan, V Raychoudhury… | 2023 | ACM Computing … | dl.acm.org | 167 | 55.666666666666664 |
| 127 | From pinns to pikans: Recent advances in physics-informed machine learning | JD Toscano, V Oommen, AJ Varghese, Z Zou… | 2025 | Machine Learning for … | Springer | 112 | 112.0 |
| 128 | [HTML][HTML] A comprehensive review of the applications of machine learning for HVAC | SL Zhou, AA Shah, PK Leung, X Zhu, Q Liao | 2023 | DeCarbon | Elsevier | 78 | 26.0 |
| 129 | Machine learning-guided protein engineering | P Kouba, P Kohout, F Haddadi, A Bushuiev… | 2023 | ACS … | ACS Publications | 136 | 45.333333333333336 |
| 130 | A systematic review of machine learning methods in software testing | S Ajorloo, A Jamarani, M Kashfi, MH Kashani… | 2024 | Applied Soft … | Elsevier | 31 | 15.5 |
| 131 | From patterns to patients: Advances in clinical machine learning for cancer diagnosis, prognosis, and treatment | K Swanson, E Wu, A Zhang, AA Alizadeh, J Zou | 2023 | Cell | cell.com | 435 | 145.0 |
| 132 | [HTML][HTML] Soil science-informed machine learning | B Minasny, T Bandai, TA Ghezzehei, YC Huang, Y Ma… | 2024 | Geoderma | Elsevier | 41 | 20.5 |
| 133 | The transformative potential of machine learning for experiments in fluid mechanics | R Vinuesa, SL Brunton, BJ McKeon | 2023 | Nature Reviews Physics | nature.com | 109 | 36.333333333333336 |
| 134 | The benefits and pitfalls of machine learning for biomarker discovery | S Ng, S Masarone, D Watson, MR Barnes | 2023 | Cell and tissue research | Springer | 118 | 39.333333333333336 |
| 135 | [BOOK][B] Machine learning: concepts, techniques and applications | TV Geetha, S Sendhilkumar | 2023 | 2023 | taylorfrancis.com | 39 | 13.0 |
| 136 | Stop ordering machine learning algorithms by their explainability! A user-centered investigation of performance and explainability | LV Herm, K Heinrich, J Wanner, C Janiesch | 2023 | International Journal of … | Elsevier | 159 | 53.0 |
| 137 | Predicting E-commerce customer satisfaction: Traditional machine learning vs. deep learning approaches | M Zaghloul, S Barakat, A Rezk | 2024 | Journal of Retailing and Consumer … | Elsevier | 50 | 25.0 |
| 138 | [HTML][HTML] Bias in machine learning: A literature review | K Mavrogiorgos, A Kiourtis, A Mavrogiorgou… | 2024 | Applied Sciences | mdpi.com | 53 | 26.5 |
| 139 | Application of machine learning in groundwater quality modeling-A comprehensive review | R Haggerty, J Sun, H Yu, Y Li | 2023 | Water Research | Elsevier | 238 | 79.33333333333333 |
| 140 | Applications and techniques of machine learning in cancer classification: a systematic review | A Yaqoob, R Musheer Aziz, NK Verma | 2023 | Centric Intelligent … | Springer | 110 | 36.666666666666664 |
| 141 | [HTML][HTML] Comparative analysis for slope stability by using machine learning methods | YA Nanehkaran, Z Licai, J Chengyong, J Chen… | 2023 | Applied Sciences | mdpi.com | 109 | 36.333333333333336 |
| 142 | Can we predict T cell specificity with digital biology and machine learning? | D Hudson, RA Fernandes, M Basham, G Ogg… | 2023 | Nature Reviews … | nature.com | 184 | 61.333333333333336 |
| 143 | Revolutionizing healthcare: the role of machine learning in the health sector | M Sarker | 2024 | Journal of Artificial Intelligence General science (JAIGS … | ideas.repec.org | 71 | 35.5 |
| 144 | A comprehensive review of machine learning algorithms and their application in geriatric medicine: present and future | RJ Woodman, AA Mangoni | 2023 | Aging Clinical and Experimental Research | Springer | 114 | 38.0 |
| 145 | IoT convergence with machine learning & blockchain: A review | E Fazel, MZ Nezhad, J Rezazadeh, M Moradi… | 2024 | Internet of Things | Elsevier | 42 | 21.0 |
| 146 | [HTML][HTML] Application of machine learning in material synthesis and property prediction | G Huang, Y Guo, Y Chen, Z Nie | 2023 | Materials | mdpi.com | 90 | 30.0 |
| 147 | Rediscovering orbital mechanics with machine learning | P Lemos, N Jeffrey, M Cranmer, S Ho… | 2023 | Machine Learning … | iopscience.iop.org | 141 | 47.0 |
| 148 | Machine learning and the politics of synthetic data | BN Jacobsen | 2023 | Big Data & Society | journals.sagepub.com | 85 | 28.333333333333332 |
| 149 | Machine learning in nanozymes: from design to application | Y Gao, Z Zhu, Z Chen, M Guo, Y Zhang, L Wang… | 2024 | Biomaterials … | pubs.rsc.org | 25 | 12.5 |
| 150 | Machine learning applications in nanomaterials: Recent advances and future perspectives | L Yang, H Wang, D Leng, S Fang, Y Yang… | 2024 | Chemical Engineering … | Elsevier | 54 | 27.0 |
| 151 | [HTML][HTML] Interpretable machine learning for building energy management: A state-of-the-art review | Z Chen, F Xiao, F Guo, J Yan | 2023 | Advances in Applied Energy | Elsevier | 268 | 89.33333333333333 |
| 152 | Automating Cybersecurity with Machine Learning and Predictive Analytics | GK Karamchand | 2023 | Journal of Computational Innovation | researchworkx.com | 117 | 39.0 |
| 153 | A review of machine learning applications in life cycle assessment studies | XX Romeiko, X Zhang, Y Pang, F Gao, M Xu… | 2024 | Science of The Total … | Elsevier | 66 | 33.0 |
| 154 | [HTML][HTML] Machine learning for anomaly detection in particle physics | V Belis, P Odagiu, TK Aarrestad | 2024 | Reviews in Physics | Elsevier | 76 | 38.0 |
| 155 | Accelerating the prediction of stable materials with machine learning | SD Griesemer, Y Xia, C Wolverton | 2023 | Nature Computational Science | nature.com | 67 | 22.333333333333332 |
| 156 | [HTML][HTML] Precision machine learning | EJ Michaud, Z Liu, M Tegmark | 2023 | Entropy | mdpi.com | 60 | 20.0 |
| 157 | Leaf disease detection using machine learning and deep learning: Review and challenges | C Sarkar, D Gupta, U Gupta, BB Hazarika | 2023 | Applied Soft Computing | Elsevier | 199 | 66.33333333333333 |
| 158 | The significance of machine learning and deep learning techniques in cybersecurity: A comprehensive review | MM Mijwil, IE Salem… | 2023 | Iraqi Journal For … | ijcsm.researchcommons.org | 148 | 49.333333333333336 |
| 159 | [HTML][HTML] Review of machine learning in robotic grasping control in space application | H Jahanshahi, ZH Zhu | 2024 | Acta Astronautica | Elsevier | 71 | 35.5 |
| 160 | [HTML][HTML] Machine learning-based predictive models for detection of cardiovascular diseases | A Ogunpola, F Saeed, S Basurra, AM Albarrak… | 2024 | Diagnostics | mdpi.com | 164 | 82.0 |
| 161 | Progress and opportunities for machine learning in materials and processes of additive manufacturing | WL Ng, GL Goh, GD Goh, JSJ Ten… | 2024 | Advanced … | Wiley Online Library | 160 | 80.0 |
| 162 | [BOOK][B] Applications of artificial neural networks and machine learning in civil engineering | A Kaveh | 2024 | 2024 | Springer | 262 | 131.0 |
| 163 | Characterizing uncertainty in machine learning for chemistry | E Heid, CJ McGill, FH Vermeire… | 2023 | Journal of Chemical … | ACS Publications | 67 | 22.333333333333332 |
| 164 | [HTML][HTML] Machine learning and artificial intelligence in neuroscience: A primer for researchers | F Badrulhisham, E Pogatzki | 2024 | Brain | Elsevier | 74 | 37.0 |
| 165 | A practical guide to machine learning interatomic potentials–Status and future | R Jacobs, D Morgan, S Attarian, J Meng, C Shen… | 2025 | Current Opinion in Solid … | Elsevier | 63 | 63.0 |
| 166 | [HTML][HTML] Battery safety: Machine learning-based prognostics | J Zhao, X Feng, Q Pang, M Fowler, Y Lian… | 2024 | Progress in Energy and … | Elsevier | 135 | 67.5 |
| 167 | Machine learning methodology for identifying vehicles using image processing | M Hasanvand, M Nooshyar… | 2023 | Artificial Intelligence … | ojs.bonviewpress.com | 142 | 47.333333333333336 |
| 168 | From prediction to design: recent advances in machine learning for the study of 2D materials | H He, Y Wang, Y Qi, Z Xu, Y Li, Y Wang | 2023 | Nano Energy | Elsevier | 76 | 25.333333333333332 |
| 169 | Weakly supervised machine learning | Z Ren, S Wang, Y Zhang | 2023 | CAAI Transactions on Intelligence … | Wiley Online Library | 146 | 48.666666666666664 |
| 170 | [PDF][PDF] A tutorial on principal component analysis for dimensionality reduction in machine learning | JP Bharadiya | 2023 | International journal of innovative science and … | academia.edu | 141 | 47.0 |
| 171 | Machine learning and deep learning—A review for ecologists | M Pichler, F Hartig | 2023 | Methods in Ecology and Evolution | Wiley Online Library | 334 | 111.33333333333333 |
| 172 | Machine learning for micro-and nanorobots | L Yang, J Jiang, F Ji, Y Li, KL Yung, A Ferreira… | 2024 | Nature Machine … | nature.com | 60 | 30.0 |
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| 174 | A dependable hybrid machine learning model for network intrusion detection | MA Talukder, KF Hasan, MM Islam, MA Uddin… | 2023 | Journal of Information … | Elsevier | 250 | 83.33333333333333 |
| 175 | [PDF][PDF] AI and Machine Learning in Cybersecurity: Strategies, Threats, and Exploits | A Mohammed | 2023 | Innovative Computer Sciences Journal | academia.edu | 117 | 39.0 |
| 176 | Using machine learning to individualize treatment effect estimation: challenges and opportunities | A Curth, RW Peck, E McKinney… | 2024 | Clinical … | Wiley Online Library | 33 | 16.5 |
| 177 | [HTML][HTML] Applications of artificial intelligence, machine learning, and deep learning in nutrition: A systematic review | TP Theodore Armand, KA Nfor, JI Kim, HC Kim | 2024 | Nutrients | mdpi.com | 78 | 39.0 |
| 178 | Catalysis in the digital age: Unlocking the power of data with machine learning | BM Abraham, MV Jyothirmai, P Sinha… | 2024 | Wiley … | Wiley Online Library | 37 | 18.5 |
| 179 | Physics-informed machine learning for reliability and systems safety applications: State of the art and challenges | Y Xu, S Kohtz, J Boakye, P Gardoni, P Wang | 2023 | Reliability Engineering & … | Elsevier | 301 | 100.33333333333333 |
| 180 | Crop yield prediction using machine learning techniques | S Iniyan, VA Varma, CT Naidu | 2023 | Advances in Engineering Software | Elsevier | 159 | 53.0 |
| 181 | [HTML][HTML] Application of machine learning for composite moulding process modelling | Y Wang, S Xu, KH Bwar, B Eisenbart, G Lu… | 2024 | Composites … | Elsevier | 55 | 27.5 |
| 182 | [PDF][PDF] Review of predictive modeling and machine learning applications in financial service analysis | KJ Olowe, NL Edoh, SJC Zouo… | 2024 | Computer Science & IT … | researchgate.net | 24 | 12.0 |
| 183 | High-throughput microbial culturomics using automation and machine learning | Y Huang, RU Sheth, S Zhao, LA Cohen… | 2023 | Nature … | nature.com | 203 | 67.66666666666667 |
| 184 | [HTML][HTML] A survey of applications of artificial intelligence and machine learning in future mobile networks-enabled systems | İ Yazici, I Shayea, J Din | 2023 | … Science and Technology | Elsevier | 121 | 40.333333333333336 |
| 185 | [HTML][HTML] Predicting the onset of diabetes with machine learning methods | CY Chou, DY Hsu, CH Chou | 2023 | Journal of Personalized Medicine | mdpi.com | 138 | 46.0 |
| 186 | Applications of artificial intelligence, machine learning, and deep learning in nutrition: a systematic review | TPT Armand, KA Nfor, JI Kim, HC Kim | 2024 | Nutrients | pmc.ncbi.nlm.nih.gov | 75 | 37.5 |
| 187 | A machine learning explainability tutorial for atmospheric sciences | ML Flora, CK Potvin, A McGovern… | 2024 | Artificial Intelligence for … | journals.ametsoc.org | 49 | 24.5 |
| 188 | Bridging the complexity gap in computational heterogeneous catalysis with machine learning | T Mou, HS Pillai, S Wang, M Wan, X Han… | 2023 | Nature Catalysis | nature.com | 199 | 66.33333333333333 |
| 189 | Chatgpt or human? detect and explain. explaining decisions of machine learning model for detecting short chatgpt-generated text | S Mitrović, D Andreoletti, O Ayoub | 2023 | arXiv preprint arXiv:2301.13852 | arxiv.org | 245 | 81.66666666666667 |
| 190 | Enhancing Marketing, Sales, Innovation, and Financial Management Through Machine Learning | SKC Tulli | 2023 | International Journal of Modern Computing | yuktabpublisher.com | 115 | 38.333333333333336 |
| 191 | [HTML][HTML] Forecasting stock market prices using machine learning and deep learning models: A systematic review, performance analysis and discussion of implications | G Sonkavde, DS Dharrao, AM Bongale… | 2023 | International Journal of … | mdpi.com | 257 | 85.66666666666667 |
| 192 | [HTML][HTML] Fraud detection in healthcare claims using machine learning: A systematic review | A du Preez, S Bhattacharya, P Beling… | 2025 | Artificial Intelligence in … | Elsevier | 14 | 14.0 |
| 193 | Shield attitude prediction based on Bayesian-LGBM machine learning | H Chen, X Li, Z Feng, L Wang, Y Qin, MJ Skibniewski… | 2023 | Information … | Elsevier | 107 | 35.666666666666664 |
| 194 | [HTML][HTML] A systematic review of the literature on machine learning application of determining the attributes influencing academic performance | I Issah, O Appiah, P Appiahene, F Inusah | 2023 | Decision analytics journal | Elsevier | 107 | 35.666666666666664 |
| 195 | Uncertainty quantification in scientific machine learning: Methods, metrics, and comparisons | AF Psaros, X Meng, Z Zou, L Guo… | 2023 | Journal of Computational … | Elsevier | 421 | 140.33333333333334 |
| 196 | [PDF][PDF] Techniques and applications of Machine Learning and Artificial Intelligence in education: a systematic review | W Forero | 2024 | Revista Iberoamericana de … | redalyc.org | 106 | 53.0 |
| 197 | [HTML][HTML] Condition monitoring using machine learning: A review of theory, applications, and recent advances | O Surucu, SA Gadsden, J Yawney | 2023 | Expert Systems with Applications | Elsevier | 269 | 89.66666666666667 |
| 198 | Machine learning aided design and optimization of thermal metamaterials | C Zhu, EA Bamidele, X Shen, G Zhu, B Li | 2024 | Chemical Reviews | ACS Publications | 79 | 39.5 |
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| 200 | Quantum machine learning in healthcare: Developments and challenges | S Rani, PK Pareek, J Kaur, M Chauhan… | 2023 | … on Integrated Circuits … | ieeexplore.ieee.org | 102 | 34.0 |
| 201 | [HTML][HTML] Machine learning meets cancer | EV Varlamova, MA Butakova, VV Semyonova… | 2024 | Cancers | mdpi.com | 27 | 13.5 |
| 202 | [HTML][HTML] Chronic kidney disease prediction based on machine learning algorithms | MA Islam, MZH Majumder, MA Hussein | 2023 | Journal of pathology informatics | Elsevier | 245 | 81.66666666666667 |
| 203 | Machine learning and artificial intelligence in research and healthcare | L Rubinger, A Gazendam, S Ekhtiari, M Bhandari | 2023 | Injury | Elsevier | 190 | 63.333333333333336 |
| 204 | Spikingjelly: An open-source machine learning infrastructure platform for spike-based intelligence | W Fang, Y Chen, J Ding, Z Yu, T Masquelier… | 2023 | Science … | science.org | 383 | 127.66666666666667 |
| 205 | [PDF][PDF] Machine Learning in Credit Risk Assessment: Analyzing How Machine Learning Models Are | TR Gatla | 2023 | International Journal of Emerging Technologies and … | researchgate.net | 58 | 19.333333333333332 |
| 206 | Healthcare predictive analytics using machine learning and deep learning techniques: a survey | M Badawy, N Ramadan, HA Hefny | 2023 | Journal of Electrical Systems and … | Springer | 210 | 70.0 |
| 207 | Machine learning and AI in cancer prognosis, prediction, and treatment selection: a critical approach | B Zhang, H Shi, H Wang | 2023 | Journal of multidisciplinary healthcare | Taylor & Francis | 274 | 91.33333333333333 |
| 208 | The Emergence of Artificial Intelligence and Machine Learning in Contemporary Business Management | P William, A Panicker, A Falah… | 2023 | 2023 4th … | ieeexplore.ieee.org | 69 | 23.0 |
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| 212 | Phase transition study meets machine learning | YG Ma, LG Pang, R Wang, K Zhou | 2023 | Chinese Physics Letters | iopscience.iop.org | 53 | 17.666666666666668 |
| 213 | A systematic review and meta-analysis of machine learning, deep learning, and ensemble learning approaches in predicting EV charging behavior | E Yaghoubi, E Yaghoubi, A Khamees, D Razmi… | 2024 | … Applications of Artificial … | Elsevier | 124 | 62.0 |
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| 216 | [HTML][HTML] Forecasting renewable energy generation with machine learning and deep learning: Current advances and future prospects | NE Benti, MD Chaka, AG Semie | 2023 | Sustainability | mdpi.com | 245 | 81.66666666666667 |
| 217 | Machine learning for high-entropy alloys: Progress, challenges and opportunities | X Liu, J Zhang, Z Pei | 2023 | Progress in Materials Science | Elsevier | 308 | 102.66666666666667 |
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| 220 | Mechanism for feature learning in neural networks and backpropagation-free machine learning models | A Radhakrishnan, D Beaglehole, P Pandit, M Belkin | 2024 | Science | science.org | 77 | 38.5 |
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| 222 | Integrating physics-based modeling with machine learning for lithium-ion batteries | H Tu, S Moura, Y Wang, H Fang | 2023 | Applied energy | Elsevier | 146 | 48.666666666666664 |
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| 224 | Application of machine learning in optical fiber sensors | Y Zhou, Y Zhang, Q Yu, L Ren, Q Liu, Y Zhao | 2024 | Measurement | Elsevier | 51 | 25.5 |
| 225 | [HTML][HTML] Democratizing artificial intelligence: How no-code AI can leverage machine learning operations | L Sundberg, J Holmström | 2023 | Business Horizons | Elsevier | 147 | 49.0 |
| 226 | Machine learning heralding a new development phase in molecular dynamics simulations | E Prašnikar, M Ljubič, A Perdih, J Borišek | 2024 | Artificial intelligence review | Springer | 63 | 31.5 |
| 227 | [PDF][PDF] The role of machine learning in transforming business intelligence | JP Bharadiya | 2023 | International Journal of Computing and Artificial … | academia.edu | 104 | 34.666666666666664 |
| 228 | [HTML][HTML] MRI brain tumor detection using deep learning and machine learning approaches | S Anantharajan, S Gunasekaran, T Subramanian | 2024 | Measurement … | Elsevier | 139 | 69.5 |
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| 230 | High-energy nuclear physics meets machine learning | WB He, YG Ma, LG Pang, HC Song, K Zhou | 2023 | Nuclear Science and … | Springer | 96 | 32.0 |
| 231 | Using machine-learning models to understand nonlinear relationships between land use and travel | J Cao, T Tao | 2023 | Transportation Research Part D: Transport and … | Elsevier | 65 | 21.666666666666668 |
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| 236 | Recent advances in machine learning‐assisted multiscale design of energy materials | B Mortazavi | 2025 | Advanced Energy Materials | Wiley Online Library | 65 | 65.0 |
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| 239 | Machine learning techniques for breast cancer prediction | V Nemade, V Fegade | 2023 | Procedia Computer Science | Elsevier | 98 | 32.666666666666664 |
| 240 | MRI-based brain tumor detection using convolutional deep learning methods and chosen machine learning techniques | S Saeedi, S Rezayi, H Keshavarz… | 2023 | BMC Medical Informatics … | Springer | 490 | 163.33333333333334 |
| 241 | Learning machine learning with young children: Exploring informal settings in an African context | IT Sanusi, K Sunday, SS Oyelere… | 2024 | Computer Science … | Taylor & Francis | 35 | 17.5 |
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| 245 | [HTML][HTML] Metallogenic prediction based on fractal theory and machine learning in Duobaoshan Area, Heilongjiang Province | J Chen, Z Zhao, Y Yang, C Li, Y Yin, X Zhao, N Zhao… | 2024 | Ore Geology … | Elsevier | 42 | 21.0 |
| 246 | Improving soil moisture prediction with deep learning and machine learning models | FT Teshome, HK Bayabil, B Schaffer… | 2024 | … and Electronics in … | Elsevier | 39 | 19.5 |
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| 251 | Predictions of steel price indices through machine learning for the regional northeast Chinese market | B Jin, X Xu | 2024 | Neural computing and applications | Springer | 136 | 68.0 |
| 252 | Predicting potato crop yield with machine learning and deep learning for sustainable agriculture | ESM El | 2025 | Potato Research | Springer | 81 | 81.0 |
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| 257 | Machine Learning in Motion: Real-World Implementations and Future Possibilities | AS Shethiya | 2023 | Academia Nexus Journal | academianexusjournal.com | 31 | 10.333333333333334 |
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| 263 | Applications of machine learning techniques for enhancing nondestructive food quality and safety detection | Y Lin, J Ma, Q Wang, DW Sun | 2023 | Critical Reviews in Food Science … | Taylor & Francis | 176 | 58.666666666666664 |
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| 265 | Personalized adaptive learning technologies based on machine learning techniques to identify learning styles: A systematic literature review | SG Essa, T Celik, NE Human | 2023 | IEEE Access | ieeexplore.ieee.org | 234 | 78.0 |
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| 267 | Artificial intelligence and machine learning for drug safety | YM Al | 2023 | Technology for drug safety: Current status and future … | Springer | 100 | 33.333333333333336 |
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| 285 | Machine learning in crime prediction | K Jenga, C Catal, G Kar | 2023 | Journal of Ambient Intelligence and Humanized … | Springer | 105 | 35.0 |
| 286 | [HTML][HTML] Assessing the influence of sugarcane bagasse ash for the production of eco-friendly concrete: Experimental and machine learning approaches | MHR Sobuz, SD Datta, JA Jabin, FS Aditto… | 2024 | Case Studies in … | Elsevier | 90 | 45.0 |
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| 291 | A survey for solving mixed integer programming via machine learning | J Zhang, C Liu, X Li, HL Zhen, M Yuan, Y Li, J Yan | 2023 | Neurocomputing | Elsevier | 147 | 49.0 |
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| 320 | Machine learning in precision diabetes care and cardiovascular risk prediction | EK Oikonomou, R Khera | 2023 | Cardiovascular Diabetology | Springer | 121 | 40.333333333333336 |
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| 447 | Recent endeavors in machine learning-powered intrusion detection systems for the internet of things | D Manivannan | 2024 | Journal of Network and Computer Applications | Elsevier | 35 | 17.5 |
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| 449 | Machine learning interatomic potentials and long-range physics | DM Anstine, O Isayev | 2023 | The Journal of Physical Chemistry A | ACS Publications | 179 | 59.666666666666664 |
| 450 | Predicting coronary heart disease in Chinese diabetics using machine learning | CY Ma, YM Luo, TY Zhang, YD Hao, XQ Xie… | 2024 | Computers in Biology … | Elsevier | 38 | 19.0 |
| 451 | Recent advances in algal bloom detection and prediction technology using machine learning | J Park, K Patel, WH Lee | 2024 | Science of The Total Environment | Elsevier | 41 | 20.5 |
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| 454 | Comprehensive review of machine learning in geotechnical reliability analysis: Algorithms, applications and further challenges | W Zhang, X Gu, L Hong, L Han, L Wang | 2023 | Applied Soft Computing | Elsevier | 148 | 49.333333333333336 |
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| 456 | Classification prediction of breast cancer based on machine learning | H Chen, N Wang, X Du, K Mei… | 2023 | Computational … | Wiley Online Library | 114 | 38.0 |
| 457 | Overview on intrusion detection systems design exploiting machine learning for networking cybersecurity | P Dini, A Elhanashi, A Begni, S Saponara, Q Zheng… | 2023 | Applied Sciences | mdpi.com | 146 | 48.666666666666664 |
| 458 | Optimizing classification efficiency with machine learning techniques for pattern matching | BA Hamed, OAS Ibrahim, T Abd El | 2023 | Journal of Big Data | Springer | 53 | 17.666666666666668 |
| 459 | Cloud-based intrusion detection approach using machine learning techniques | H Attou, A Guezzaz, S Benkirane… | 2023 | Big Data Mining and … | ieeexplore.ieee.org | 127 | 42.333333333333336 |
| 460 | A comprehensive review of quantum machine learning: from nisq to fault tolerance | Y Wang, J Liu | 2024 | Reports on Progress in Physics | iopscience.iop.org | 75 | 37.5 |
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| 463 | Improving machine learning with ensemble learning on observational healthcare data | B Naderalvojoud… | 2024 | AMIA Annual … | pmc.ncbi.nlm.nih.gov | 45 | 22.5 |
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| 465 | Chinese diabetes datasets for data-driven machine learning | Q Zhao, J Zhu, X Shen, C Lin, Y Zhang, Y Liang, B Cao… | 2023 | Scientific Data | nature.com | 61 | 20.333333333333332 |
| 466 | [HTML][HTML] Integration of remote sensing and machine learning for precision agriculture: a comprehensive perspective on applications | J Wang, Y Wang, G Li, Z Qi | 2024 | Agronomy | mdpi.com | 55 | 27.5 |
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| 468 | A review on analysis of k-means clustering machine learning algorithm based on unsupervised learning | M Suyal, S Sharma | 2024 | Journal of Artificial Intelligence and Systems | iecscience.org | 31 | 15.5 |
| 469 | [HTML][HTML] Machine learning methods for cancer classification using gene expression data: A review | F Alharbi, A Vakanski | 2023 | Bioengineering | mdpi.com | 192 | 64.0 |
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| 472 | [HTML][HTML] Internet of Intelligent Things: A convergence of embedded systems, edge computing and machine learning | F Oliveira, DG Costa, F Assis, I Silva | 2024 | Internet of Things | Elsevier | 124 | 62.0 |
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| 474 | Hybrid modeling of first-principles and machine learning: A step-by-step tutorial review for practical implementation | P Shah, S Pahari, R Bhavsar, JSI Kwon | 2025 | Computers & Chemical … | Elsevier | 40 | 40.0 |
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| 477 | Quantum data encoding: A comparative analysis of classical-to-quantum mapping techniques and their impact on machine learning accuracy | M Rath, H Date | 2024 | EPJ Quantum Technology | epjqt.epj.org | 77 | 38.5 |
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| 479 | Machine learning-driven optimization of enterprise resource planning (ERP) systems: a comprehensive review | ZN Jawad, V Balázs | 2024 | Suef University Journal of Basic and Applied … | Springer | 120 | 60.0 |
| 480 | [HTML][HTML] Air Quality Index prediction using machine learning for Ahmedabad city | NN Maltare, S Vahora | 2023 | Digital Chemical Engineering | Elsevier | 115 | 38.333333333333336 |
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| 482 | [HTML][HTML] Prediction of the severity of marine accidents using improved machine learning | Y Feng, X Wang, Q Chen, Z Yang, J Wang, H Li… | 2024 | … Research Part E … | Elsevier | 49 | 24.5 |
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| 493 | Machine learning and deep learning predictive models for long-term prognosis in patients with chronic obstructive pulmonary disease: a systematic review and meta … | LA Smith, L Oakden | 2023 | The Lancet Digital … | thelancet.com | 63 | 21.0 |
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| 500 | [HTML][HTML] Machine learning for small molecule drug discovery in academia and industry | A Volkamer, S Riniker, E Nittinger, J Lanini… | 2023 | Artificial Intelligence in … | Elsevier | 51 | 17.0 |
| 501 | [HTML][HTML] Soft electronics for health monitoring assisted by machine learning | Y Qiao, J Luo, T Cui, H Liu, H Tang, Y Zeng, C Liu… | 2023 | Micro Letters | Springer | 86 | 28.666666666666668 |
| 502 | Active machine learning model for the dynamic simulation and growth mechanisms of carbon on metal surface | D Zhang, P Yi, X Lai, L Peng, H Li | 2024 | Nature Communications | nature.com | 44 | 22.0 |
| 503 | [HTML][HTML] Blockchain and machine learning for future smart grids: A review | VK Mololoth, S Saguna, C Åhlund | 2023 | Energies | mdpi.com | 105 | 35.0 |
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| 510 | Machine learning and deep learning approach for medical image analysis: diagnosis to detection | M Rana, M Bhushan | 2023 | Multimedia Tools and Applications | Springer | 342 | 114.0 |
| 511 | Machine learning-based marker for coronary artery disease: derivation and validation in two longitudinal cohorts | IS Forrest, BO Petrazzini, Á Duffy, JK Park… | 2023 | The Lancet | thelancet.com | 143 | 47.666666666666664 |
| 512 | [HTML][HTML] Detecting phishing domains using machine learning | S Alnemari, M Alshammari | 2023 | Applied Sciences | mdpi.com | 111 | 37.0 |
| 513 | Data-driven science and machine learning methods in laser–plasma physics | A Döpp, C Eberle, S Howard, F Irshad, J Lin… | 2023 | High Power Laser … | cambridge.org | 116 | 38.666666666666664 |
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| 527 | A survey of the opportunities and challenges of supervised machine learning in maritime risk analysis | A Rawson, M Brito | 2023 | Transport Reviews | Taylor & Francis | 115 | 38.333333333333336 |
| 528 | Machine learning-enhanced flexible mechanical sensing | Y Wang, ML Adam, Y Zhao, W Zheng, L Gao, Z Yin… | 2023 | Micro Letters | Springer | 134 | 44.666666666666664 |
| 529 | Trends and potential of machine learning and deep learning in drug study at single-cell level | R Qi, Q Zou | 2023 | Research | spj.science.org | 62 | 20.666666666666668 |
| 530 | Machine learning–driven SERS nanoendoscopy and optophysiology | M Chisanga, JF Masson | 2024 | Annual Review of Analytical Chemistry | annualreviews.org | 17 | 8.5 |
| 531 | [PDF][PDF] Parallel machine learning algorithms | SA Salman, SA Dheyab… | 2023 | … Journal of Big … | journals.mesopotamian.press | 23 | 7.666666666666667 |
| 532 | Machine learning: a new approach for dose individualization | QY Li, BH Tang, YE Wu, BF Yao… | 2024 | Clinical … | Wiley Online Library | 36 | 18.0 |
| 533 | News-based intelligent prediction of financial markets using text mining and machine learning: A systematic literature review | MN Ashtiani, B Raahemi | 2023 | Expert Systems with Applications | Elsevier | 178 | 59.333333333333336 |
| 534 | A review on recent developments in cancer detection using machine learning and deep learning models | S Maurya, S Tiwari, MC Mothukuri, CM Tangeda… | 2023 | … Signal Processing and … | Elsevier | 101 | 33.666666666666664 |
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| 540 | Incorporating sparse model machine learning in designing cultural heritage landscapes | P Goodarzi, M Ansari, FP Rahimian… | 2023 | Automation in … | Elsevier | 35 | 11.666666666666666 |
| 541 | AI and machine learning for soil analysis: an assessment of sustainable agricultural practices | M Awais, SMZA Naqvi, H Zhang, L Li, W Zhang… | 2023 | Bioresources and … | Springer | 61 | 20.333333333333332 |
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| 545 | [HTML][HTML] Machine learning for forecasting a photovoltaic (PV) generation system | C Scott, M Ahsan, A Albarbar | 2023 | Energy | Elsevier | 121 | 40.333333333333336 |
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| 551 | Mlatom 3: A platform for machine learning-enhanced computational chemistry simulations and workflows | PO Dral, F Ge, YF Hou, P Zheng, Y Chen… | 2024 | Journal of Chemical … | ACS Publications | 51 | 25.5 |
| 552 | Hybrid LBM and machine learning algorithms for permeability prediction of porous media: A comparative study | Q Kang, KQ Li, JL Fu, Y Liu | 2024 | Computers and Geotechnics | Elsevier | 42 | 21.0 |
| 553 | Machine learning in cardiology: Clinical application and basic research | J Komuro, D Kusumoto, H Hashimoto, S Yuasa | 2023 | Journal of cardiology | Elsevier | 27 | 9.0 |
| 554 | Diabetes prediction model using machine learning techniques | SKS Modak, VK Jha | 2024 | Multimedia Tools and Applications | Springer | 60 | 30.0 |
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| 556 | Detecting ai generated text based on nlp and machine learning approaches | N Prova | 2024 | arXiv preprint arXiv:2404.10032 | arxiv.org | 80 | 40.0 |
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| 560 | Analysing Factors for Improving Pregnancy Outcomes Using Machine Learning | S Devi, A Raj, P Joshi, S Rawat | 2023 | … Issues with Machine Learning | taylorfrancis.com | 52 | 17.333333333333332 |
| 561 | Research on effectiveness evaluation and optimization of baseball teaching method based on machine learning | S Sun, J Yuan, Y Yang | 2024 | arXiv preprint arXiv:2411.15721 | arxiv.org | 30 | 15.0 |
| 562 | [HTML][HTML] … and conventional logistic regression-based prediction models for gestational diabetes in an ethnically diverse population; the Monash GDM Machine learning … | Y Belsti, L Moran, L Du, A Mousa, K De Silva… | 2023 | International Journal of … | Elsevier | 50 | 16.666666666666668 |
| 563 | A robust, agnostic molecular biosignature based on machine learning | HJ Cleaves, G Hystad, A Prabhu, ML Wong… | 2023 | Proceedings of the … | pnas.org | 28 | 9.333333333333334 |
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| 574 | [HTML][HTML] A systematic literature review on modern methods of construction in building: An integrated approach using machine learning | AJ Sánchez | 2023 | Journal of Building … | Elsevier | 106 | 35.333333333333336 |
| 575 | Cancer detection and segmentation using machine learning and deep learning techniques: A review | HM Rai | 2024 | Multimedia Tools and Applications | Springer | 66 | 33.0 |
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| 577 | Predicting electronic structures at any length scale with machine learning | L Fiedler, NA Modine, S Schmerler, DJ Vogel… | 2023 | npj Computational … | nature.com | 53 | 17.666666666666668 |
| 578 | Exploring data mining and machine learning in gynecologic oncology | F Idlahcen, A Idri, E Goceri | 2024 | Artificial Intelligence Review | Springer | 39 | 19.5 |
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| 584 | Machine learning and deep learning for user authentication and authorization in cybersecurity: A state-of-the-art review | ZT Pritee, MH Anik, SB Alam, JR Jim, MM Kabir… | 2024 | Computers & … | Elsevier | 35 | 17.5 |
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| 586 | Software defect prediction using Machine learning | S Setia, KK Ravulakollu, K Verma… | 2024 | … on Computing for … | ieeexplore.ieee.org | 92 | 46.0 |
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| 588 | Evaluation of machine learning approaches for precision farming in smart agriculture system: a comprehensive review | G Mohyuddin, MA Khan, A Haseeb, S Mahpara… | 2024 | IEEE … | ieeexplore.ieee.org | 116 | 58.0 |
| 589 | Machine learning in bioprocess development: from promise to practice | LM Helleckes, J Hemmerich, W Wiechert… | 2023 | Trends in … | cell.com | 102 | 34.0 |
| 590 | Machine learning for brain disorders | O Colliot | 2023 | 2023 | books.google.com | 44 | 14.666666666666666 |
| 591 | Blockchain security enhancement: an approach towards hybrid consensus algorithms and machine learning techniques | K Venkatesan, SB Rahayu | 2024 | Scientific Reports | nature.com | 115 | 57.5 |
| 592 | Predicting individual learning performance using machine‐learning hybridized with the teaching‐learning‐based optimization | M Arashpour, EM Golafshani… | 2023 | Computer … | Wiley Online Library | 77 | 25.666666666666668 |
| 593 | Machine learning scopes on microgrid predictive maintenance: Potential frameworks, challenges, and prospects | MY Arafat, MJ Hossain, MM Alam | 2024 | Renewable and Sustainable Energy … | Elsevier | 88 | 44.0 |
| 594 | Machine learning potentials for metal-organic frameworks using an incremental learning approach | S Vandenhaute, M Cools | 2023 | npj Computational … | nature.com | 105 | 35.0 |
| 595 | [HTML][HTML] Teaching machine learning in K–12 using robotics | G Karalekas, S Vologiannidis, J Kalomiros | 2023 | Education Sciences | mdpi.com | 31 | 10.333333333333334 |
| 596 | Machine learning for partial differential equations | SL Brunton, JN Kutz | 2023 | arXiv preprint arXiv:2303.17078 | arxiv.org | 33 | 11.0 |
| 597 | Implementation of machine learning classification techniques for intrusion detection system | P William, VNR Inukollu, V Ramasamy… | 2023 | 2023 4th … | ieeexplore.ieee.org | 60 | 20.0 |
| 598 | Interpretability of machine learning: Recent advances and future prospects | L Gao, L Guan | 2023 | IEEE MultiMedia | ieeexplore.ieee.org | 61 | 20.333333333333332 |
| 599 | Reciprocal human-machine learning: A theory and an instantiation for the case of message classification | D Te'eni, I Yahav, A Zagalsky… | 2023 | Management … | pubsonline.informs.org | 51 | 17.0 |
| 600 | A comprehensive empirical study of bias mitigation methods for machine learning classifiers | Z Chen, JM Zhang, F Sarro, M Harman | 2023 | ACM transactions on software … | dl.acm.org | 117 | 39.0 |
| 601 | Machine learning for synergistic network pharmacology: a comprehensive overview | F Noor, M Asif, UA Ashfaq, M Qasim… | 2023 | Briefings in … | academic.oup.com | 134 | 44.666666666666664 |
| 602 | Emergence of a resonance in machine learning | ZM Zhai, LW Kong, YC Lai | 2023 | Physical Review Research | APS | 38 | 12.666666666666666 |
| 603 | DDoS attacks detection using machine learning and deep learning techniques: analysis and comparison | MA Al | 2023 | Bulletin of Electrical … | journal.beei.org | 119 | 39.666666666666664 |
| 604 | [PDF][PDF] Analysing the impact of advanced analytics on fraud detection: a machine learning perspective | OA Bello, A Folorunso, J Onwuchekwa… | 2023 | European Journal of … | researchgate.net | 141 | 47.0 |
| 605 | [HTML][HTML] Machine learning techniques to detect a DDoS attack in SDN: A systematic review | TE Ali, YW Chong, S Manickam | 2023 | Applied Sciences | mdpi.com | 177 | 59.0 |
| 606 | IntelliGenes: a novel machine learning pipeline for biomarker discovery and predictive analysis using multi-genomic profiles | W DeGroat, D Mendhe, A Bhusari, H Abdelhalim… | 2023 | … | academic.oup.com | 142 | 47.333333333333336 |
| 607 | Comparative analysis of intrusion detection systems and machine learning-based model analysis through decision tree | Z Azam, MM Islam, MN Huda | 2023 | Ieee Access | ieeexplore.ieee.org | 225 | 75.0 |
| 608 | [HTML][HTML] A performance analysis of dimensionality reduction algorithms in machine learning models for cancer prediction | MF Kabir, T Chen, SA Ludwig | 2023 | Healthcare Analytics | Elsevier | 95 | 31.666666666666668 |
| 609 | Heart disease classification based on ECG using machine learning models | SM Malakouti | 2023 | Biomedical Signal Processing and Control | Elsevier | 113 | 37.666666666666664 |
| 610 | Predicting sentiment and rating of tourist reviews using machine learning | K Puh, M Bagić Babac | 2023 | Journal of hospitality and tourism insights | emerald.com | 128 | 42.666666666666664 |
| 611 | Forecasting of solar radiation using different machine learning approaches | V Demir, H Citakoglu | 2023 | Neural Computing and Applications | Springer | 121 | 40.333333333333336 |
| 612 | AI and machine learning in predictive data architecture | VK Ravi, SR Cheruku | 2024 | International Research Journal of … | papers.ssrn.com | 32 | 16.0 |
| 613 | Integrating machine learning and model predictive control for automotive applications: A review and future directions | A Norouzi, H Heidarifar, H Borhan… | 2023 | … Applications of Artificial … | Elsevier | 125 | 41.666666666666664 |
| 614 | Algorithmic collective action in machine learning | M Hardt, E Mazumdar… | 2023 | … Machine Learning | proceedings.mlr.press | 30 | 10.0 |
| 615 | Uncovering the limits of machine learning for automatic vulnerability detection | N Risse, M Böhme | 2024 | … USENIX Security Symposium (USENIX Security 24) | usenix.org | 28 | 14.0 |
| 616 | Applications of machine learning in supercritical fluids research | L Roach, GM Rignanese, A Erriguible… | 2023 | The Journal of … | Elsevier | 34 | 11.333333333333334 |
| 617 | [HTML][HTML] Novel machine learning based approach for analysing the adoption of metaverse in medical training: A UAE case study | SA Salloum, A Bettayeb, A Salloum, A Aburayya… | 2023 | Informatics in Medicine … | Elsevier | 82 | 27.333333333333332 |
| 618 | Deep learning and machine learning in psychiatry: a survey of current progress in depression detection, diagnosis and treatment | M Squires, X Tao, S Elangovan, R Gururajan, X Zhou… | 2023 | Brain Informatics | Springer | 123 | 41.0 |
| 619 | Hybrid machine learning models to detect signs of depression | S Khan, S Alqahtani | 2024 | Multimedia Tools and Applications | Springer | 49 | 24.5 |
| 620 | Using machine learning for crop yield prediction in the past or the future | A Morales, FJ Villalobos | 2023 | Frontiers in Plant Science | frontiersin.org | 124 | 41.333333333333336 |
| 621 | Current status and future directions: the application of artificial intelligence/machine learning for precision medicine | K Naik, RK Goyal, L Foschini, CW Chak… | 2024 | Clinical … | Wiley Online Library | 55 | 27.5 |
| 622 | Analysis of intrusion detection systems in UNSW-NB15 and NSL-KDD datasets with machine learning algorithms | F Türk | 2023 | Bitlis Eren Üniversitesi Fen Bilimleri Dergisi | dergipark.org.tr | 48 | 16.0 |
| 623 | A review of machine learning methods used for educational data | Z Ersozlu, S Taheri, I Koch | 2024 | Education and Information Technologies | Springer | 39 | 19.5 |
| 624 | Machine learning-assisted low-dimensional electrocatalysts design for hydrogen evolution reaction | J Li, N Wu, J Zhang, HH Wu, K Pan, Y Wang, G Liu… | 2023 | Micro Letters | Springer | 147 | 49.0 |
| 625 | Machine learning price index forecasts of flat steel products: B. Jin and X. Xu | B Jin, X Xu | 2025 | Mineral Economics | Springer | 41 | 41.0 |
| 626 | Internet of things and machine learning-integrated smart robotics | BU Maheswari, SS Imambi, D Hasan… | 2023 | igi | global.com | 63 | 21.0 |
| 627 | Medical-informed machine learning: integrating prior knowledge into medical decision systems | C Sirocchi, A Bogliolo, S Montagna | 2024 | BMC Medical Informatics and … | Springer | 47 | 23.5 |
| 628 | Machine-learning atomic simulation for heterogeneous catalysis | D Chen, C Shang, ZP Liu | 2023 | npj Computational Materials | nature.com | 72 | 24.0 |
| 629 | Advances in machine learning and deep learning applications towards wafer map defect recognition and classification: a review | T Kim, K Behdinan | 2023 | Journal of Intelligent Manufacturing | Springer | 95 | 31.666666666666668 |
| 630 | [PDF][PDF] Machine learning for intrusion detection in cloud environments: A comparative study | QO Ahmed | 2024 | Journal of Artificial Intelligence General science … | researchgate.net | 46 | 23.0 |
| 631 | [PDF][PDF] Utilizing machine learning to reassess the predictability of bank stocks | H Antonopoulou… | 2023 | Emerging Science … | pdfs.semanticscholar.org | 38 | 12.666666666666666 |
| 632 | [HTML][HTML] Analyzing sentiments regarding ChatGPT using novel BERT: A machine learning approach | M Mujahid, F Rustam, R Shafique, V Chunduri… | 2023 | Information | mdpi.com | 53 | 17.666666666666668 |
| 633 | The role of machine learning in enhancing computer vision processing | C Guo, Y Zhao, T Liu, C Yang | 2023 | … ВОПРОСЫ СОВРЕМЕННЫХ НАУЧНЫХ … | elibrary.ru | 25 | 8.333333333333334 |
| 634 | [HTML][HTML] Application of machine learning in fuel cell research | D Su, J Zheng, J Ma, Z Dong, Z Chen, Y Qin | 2023 | Energies | mdpi.com | 33 | 11.0 |
| 635 | An adaptive learning environment for programming based on fuzzy logic and machine learning | K Chrysafiadi, M Virvou, GA Tsihrintzis… | 2023 | … Journal on Artificial … | World Scientific | 42 | 14.0 |
| 636 | [HTML][HTML] Common statistical concepts in the supervised Machine Learning arena | HH Rashidi, S Albahra, S Robertson, NK Tran… | 2023 | Frontiers in … | frontiersin.org | 40 | 13.333333333333334 |
| 637 | [HTML][HTML] A machine learning approach to predicting academic performance in Pennsylvania's schools | S Chen, Y Ding | 2023 | Social Sciences | mdpi.com | 55 | 18.333333333333332 |
| 638 | ASD Diagnosis in Children, Adults, and Adolescents using Various Machine Learning Techniques | P Rawat, M Bajaj, S Vats… | 2023 | … Conference on Device … | ieeexplore.ieee.org | 42 | 14.0 |
| 639 | Informing immunotherapy with multi-omics driven machine learning | Y Li, X Wu, D Fang, Y Luo | 2024 | npj Digital Medicine | nature.com | 48 | 24.0 |
| 640 | Comparative analysis of crop diseases detection using machine learning algorithm | P Jha, D Dembla, W Dubey | 2023 | 2023 Third International … | ieeexplore.ieee.org | 79 | 26.333333333333332 |
| 641 | [HTML][HTML] Predicting maritime accident risk using Automated Machine Learning | ZH Munim, MA Sørli, H Kim, I Alon | 2024 | Reliability Engineering & System Safety | Elsevier | 52 | 26.0 |
| 642 | Examining the research taxonomy of artificial intelligence, deep learning & machine learning in the financial sphere—a bibliometric analysis | AKVN Biju, AS Thomas, J Thasneem | 2023 | Quality & Quantity | pmc.ncbi.nlm.nih.gov | 94 | 31.333333333333332 |
| 643 | A novel hybrid machine learning model for prediction of CO2 using socio-economic and energy attributes for climate change monitoring and mitigation policies | S Kumar | 2023 | Ecological informatics | Elsevier | 44 | 14.666666666666666 |
| 644 | [HTML][HTML] Effective handling of missing values in datasets for classification using machine learning methods | A Palanivinayagam, R Damaševičius | 2023 | Information | mdpi.com | 67 | 22.333333333333332 |
| 645 | [HTML][HTML] A review of hydrodynamic and machine learning approaches for flood inundation modeling | F Karim, MA Armin, D Ahmedt | 2023 | Water | mdpi.com | 106 | 35.333333333333336 |
| 646 | [HTML][HTML] Enhancing smart-contract security through machine learning: A survey of approaches and techniques | F Jiang, K Chao, J Xiao, Q Liu, K Gu, J Wu, Y Cao | 2023 | Electronics | mdpi.com | 39 | 13.0 |
| 647 | [HTML][HTML] SEM-machine learning-based model for perusing the adoption of metaverse in higher education in UAE | Y Shaalan | 2023 | International Journal of Data and Network Science | academia.edu | 125 | 41.666666666666664 |
| 648 | Comparison of three machine learning algorithms using google earth engine for land use land cover classification | Z Zhao, F Islam, LA Waseem, A Tariq, M Nawaz… | 2024 | Rangeland ecology & … | Elsevier | 198 | 99.0 |
| 649 | [HTML][HTML] Machine learning-based method for predicting compressive strength of concrete | D Li, Z Tang, Q Kang, X Zhang, Y Li | 2023 | Processes | mdpi.com | 87 | 29.0 |
| 650 | [HTML][HTML] Energy poverty prediction in the United Kingdom: A machine learning approach | D Al Kez, A Foley, ZK Abdul, DF Del Rio | 2024 | Energy Policy | Elsevier | 32 | 16.0 |
| 651 | Machine learning and deep learning for brain tumor MRI image segmentation | MKH Khan, W Guo, J Liu, F Dong, Z Li… | 2023 | Experimental … | journals.sagepub.com | 43 | 14.333333333333334 |
| 652 | [HTML][HTML] A machine learning method for the prediction of ship motion trajectories in real operational conditions | M Zhang, P Kujala, M Musharraf, J Zhang, S Hirdaris | 2023 | Ocean Engineering | Elsevier | 95 | 31.666666666666668 |
| 653 | Machine learning in radiology: the new frontier in interstitial lung diseases | H Barnes, SM Humphries, PM George… | 2023 | The Lancet Digital … | thelancet.com | 82 | 27.333333333333332 |
| 654 | Machine-learning-based monitoring and optimization of processing parameters in 3D printing | TS Tamir, G Xiong, Q Fang, Y Yang… | 2023 | … Journal of Computer … | Taylor & Francis | 100 | 33.333333333333336 |
| 655 | [HTML][HTML] Birthweight range prediction and classification: A machine learning-based sustainable approach | DA Alabbad, SY Ajibi, RB Alotaibi, NK Alsqer… | 2024 | Machine Learning and … | mdpi.com | 27 | 13.5 |
| 656 | Photonic machine learning with on-chip diffractive optics | T Fu, Y Zang, Y Huang, Z Du, H Huang, C Hu… | 2023 | Nature … | nature.com | 237 | 79.0 |
| 657 | Artificial intelligence and machine learning applications in the project lifecycle of the construction industry: A comprehensive review | SD Datta, M Islam, MHR Sobuz, S Ahmed, M Kar | 2024 | Heliyon | cell.com | 139 | 69.5 |
| 658 | [HTML][HTML] Survey of transfer learning approaches in the machine learning of digital health sensing data | L Chato, E Regentova | 2023 | Journal of personalized medicine | mdpi.com | 39 | 13.0 |
| 659 | Machine learning for enhancing transportation security: A comprehensive analysis of electric and flying vehicle systems | H Alqahtani, G Kumar | 2024 | Engineering Applications of Artificial Intelligence | Elsevier | 95 | 47.5 |
| 660 | Toward secured IoT-based smart systems using machine learning | MS Abdalzaher, MM Fouda, HA Elsayed… | 2023 | IEEE access | ieeexplore.ieee.org | 62 | 20.666666666666668 |
| 661 | Applying machine learning algorithms to predict the stock price trend in the stock market–The case of Vietnam | T Phuoc, PTK Anh, PH Tam, CV Nguyen | 2024 | Humanities and Social … | nature.com | 68 | 34.0 |
| 662 | [PDF][PDF] Involving machine learning techniques in heart disease diagnosis: a performance analysis | BS Shukur, MM Mijwil | 2023 | International Journal of Electrical and … | academia.edu | 57 | 19.0 |
| 663 | [HTML][HTML] Machine learning meets advanced robotic manipulation | S Nahavandi, R Alizadehsani, D Nahavandi, CP Lim… | 2024 | Information … | Elsevier | 28 | 14.0 |
| 664 | Applications of artificial intelligence and machine learning in the financial services industry: A bibliometric review | D Pattnaik, S Ray, R Raman | 2024 | Heliyon | cell.com | 118 | 59.0 |
| 665 | [HTML][HTML] A supervised machine learning algorithm for detecting and predicting fraud in credit card transactions | JK Afriyie, K Tawiah, WA Pels, S Addai | 2023 | Decision Analytics … | Elsevier | 187 | 62.333333333333336 |
| 666 | A review of machine learning methods applied to structural dynamics and vibroacoustic | BZ Cunha, C Droz, AM Zine, S Foulard… | 2023 | Mechanical Systems and … | Elsevier | 158 | 52.666666666666664 |
| 667 | Machine learning for human emotion recognition: a comprehensive review | EMG Younis, S Mohsen, EH Houssein… | 2024 | Neural Computing and … | Springer | 42 | 21.0 |
| 668 | [PDF][PDF] Artificial intelligence and machine learning in pharmacological research: bridging the gap between data and drug discovery | S Singh, R Kumar, S Payra, SK Singh | 2023 | Cureus | cureus.com | 157 | 52.333333333333336 |
| 669 | Machine learning in membrane design: From property prediction to AI-guided optimization | Z Cao, O Barati Farimani, J Ock, A Barati Farimani | 2024 | Nano letters | ACS Publications | 35 | 17.5 |
| 670 | Machine learning-based approach for predicting low birth weight | A Ranjbar, F Montazeri, MV Farashah… | 2023 | BMC Pregnancy and … | Springer | 39 | 13.0 |
| 671 | The smart analysis of machine learning-based diagnostics model of cardiovascular diseases in patients | J Mistry, SC Patil, B Muniandi, N Jiwani… | 2023 | … IEEE Technology & … | ieeexplore.ieee.org | 35 | 11.666666666666666 |
| 672 | {SecretFlow-SPU}: A performant and {User-Friendly} framework for {Privacy-Preserving} machine learning | J Ma, Y Zheng, J Feng, D Zhao, H Wu, W Fang… | 2023 | 2023 USeNIX annual … | usenix.org | 63 | 21.0 |
| 673 | [HTML][HTML] Machine learning for enhanced credit risk assessment: An empirical approach | N Suhadolnik, J Ueyama, S Da Silva | 2023 | Journal of Risk and Financial … | mdpi.com | 40 | 13.333333333333334 |
| 674 | [HTML][HTML] Smartfix: Leveraging machine learning for proactive equipment maintenance in industry 4.0 | F Ni, H Zang, Y Qiao | 2024 | … in education: prospects and challenges of … | books.google.com | 37 | 18.5 |
| 675 | [HTML][HTML] Electric vehicle charging system in the smart grid using different machine learning methods | T Mazhar, RN Asif, MA Malik, MA Nadeem, I Haq… | 2023 | Sustainability | mdpi.com | 135 | 45.0 |
| 676 | [HTML][HTML] A review for green energy machine learning and AI services | Y Mehta, R Xu, B Lim, J Wu, J Gao | 2023 | Energies | mdpi.com | 32 | 10.666666666666666 |
| 677 | [HTML][HTML] Systematic review identifies the design and methodological conduct of studies on machine learning-based prediction models | CLA Navarro, JAA Damen, M van Smeden… | 2023 | Journal of Clinical … | Elsevier | 96 | 32.0 |
| 678 | Artificial intelligence and machine learning for quantum technologies | M Krenn, J Landgraf, T Foesel, F Marquardt | 2023 | Physical Review A | APS | 180 | 60.0 |
| 679 | [HTML][HTML] Machine-learning-aided thermochemical treatment of biomass: a review | H Li, J Chen, W Zhang, H Zhan, C He… | 2023 | Biofuel Research … | biofueljournal.com | 109 | 36.333333333333336 |
| 680 | [HTML][HTML] Using Machine Learning to make nanomaterials sustainable | JJ Scott | 2023 | Science of The Total Environment | Elsevier | 43 | 14.333333333333334 |
| 681 | Best practices in supervised machine learning: A tutorial for psychologists | F Pargent, R Schoedel, C Stachl | 2023 | Advances in Methods and … | journals.sagepub.com | 100 | 33.333333333333336 |
| 682 | Recent developments in modeling, imaging, and monitoring of cardiovascular diseases using machine learning | H Moradi, A Al | 2023 | Biophysical … | Springer | 58 | 19.333333333333332 |
| 683 | Chemistry-informed machine learning for polymer electrolyte discovery | G Bradford, J Lopez, J Ruza, MA Stolberg… | 2023 | ACS Central … | ACS Publications | 99 | 33.0 |
| 684 | Impacts of 5G Machine Learning Techniques on Telemedicine and Social Media Professional Connection in Healthcare | PSS Sreedhar, V Sujay, MR Rani, L Melita… | 2024 | igi | global.com | 45 | 22.5 |
| 685 | Machine learning bridges omics sciences and plant breeding | J Yan, X Wang | 2023 | Trends in Plant Science | cell.com | 116 | 38.666666666666664 |
| 686 | Integrating artificial intelligence, machine learning, and deep learning approaches into remediation of contaminated sites: A review | JK Janga, KR Reddy, K Raviteja | 2023 | Chemosphere | Elsevier | 63 | 21.0 |
| 687 | Ransomware classification using btls algorithm and machine learning approaches | S Wasoye, M Stevens, C Morgan, D Hughes, J Walker | 2024 | 2024 | researchsquare.com | 67 | 33.5 |
| 688 | Hybrid‐NET: a fusion of DenseNet169 and advanced machine learning classifiers for enhanced brain tumor diagnosis | SUR Khan, M Zhao, S Asif… | 2024 | International Journal of … | Wiley Online Library | 123 | 61.5 |
| 689 | [HTML][HTML] Water quality prediction based on machine learning and comprehensive weighting methods | X Wang, Y Li, Q Qiao, A Tavares, Y Liang | 2023 | Entropy | mdpi.com | 75 | 25.0 |
| 690 | Prediction of Depression Severity and Personalised Risk Factors Using Machine Learning on Multimodal Data. | A Ayodele, A Adetunla… | 2024 | International Journal of … | search.ebscohost.com | 103 | 51.5 |
| 691 | Copyright law and the lifecycle of machine learning models | M Kretschmer, T Margoni, P Oruç | 2024 | International Review of Intellectual … | Springer | 45 | 22.5 |
| 692 | [PDF][PDF] Transforming cardiac care: AI and machine learning innovations | MT Ali, U Ali, S Ali, H Tanveer | 2024 | International … | allmultidisciplinaryjournal.com | 35 | 17.5 |
| 693 | Groundwater level forecasting with machine learning models: A review | KBW Boo, A El | 2024 | Water Research | Elsevier | 54 | 27.0 |
| 694 | [HTML][HTML] Performance analysis of the water quality index model for predicting water state using machine learning techniques | MG Uddin, S Nash, A Rahman, AI Olbert | 2023 | Process Safety and … | Elsevier | 249 | 83.0 |
| 695 | Optimizing Web Interfaces with AI-Generated CSS Through Machine Learning and Deep Learning | R Bhutia, SAK Dave, IR Mallela, R Mall… | 2024 | … on System Modeling … | ieeexplore.ieee.org | 42 | 21.0 |
| 696 | [HTML][HTML] Machine learning in clinical trials: a primer with applications to neurology | MI Miller, LC Shih, VB Kolachalama | 2023 | Neurotherapeutics | Elsevier | 46 | 15.333333333333334 |
| 697 | Topology optimization via machine learning and deep learning: a review | S Shin, D Shin, N Kang | 2023 | Journal of Computational Design and … | academic.oup.com | 137 | 45.666666666666664 |
| 698 | [HTML][HTML] Machine learning applications in optical fiber sensing: A research agenda | E Reyes | 2024 | Sensors | mdpi.com | 35 | 17.5 |
| 699 | Machine learning‐assisted property prediction of solid‐state electrolyte | J Li, M Zhou, HH Wu, L Wang, J Zhang… | 2024 | Advanced Energy … | Wiley Online Library | 100 | 50.0 |
| 700 | [HTML][HTML] Supply chain risk management with machine learning technology: A literature review and future research directions | M Yang, MK Lim, Y Qu, D Ni, Z Xiao | 2023 | Computers & Industrial Engineering | Elsevier | 132 | 44.0 |
| 701 | [HTML][HTML] Use of machine learning techniques in soil classification | Y Aydın, Ü Işıkdağ, G Bekdaş, SM Nigdeli, ZW Geem | 2023 | Sustainability | mdpi.com | 69 | 23.0 |
| 702 | RAGN-R: A multi-subject ensemble machine-learning method for estimating mechanical properties of advanced structural materials | F Kazemi, AӦ Çiftçioğlu, T Shafighfard… | 2025 | Computers & … | Elsevier | 42 | 42.0 |
| 703 | Interpretable machine learning for dementia: a systematic review | SA Martin, FJ Townend, F Barkhof… | 2023 | Alzheimer's & … | Wiley Online Library | 93 | 31.0 |
| 704 | Prediction heavy metals accumulation risk in rice using machine learning and mapping pollution risk | B Zhao, W Zhu, S Hao, M Hua, Q Liao, Y Jing… | 2023 | Journal of Hazardous … | Elsevier | 97 | 32.333333333333336 |
| 705 | Hematology and machine learning | AE Obstfeld | 2023 | The Journal of Applied Laboratory Medicine | academic.oup.com | 37 | 12.333333333333334 |
| 706 | [HTML][HTML] Machine learning-based design for additive manufacturing in biomedical engineering | C Wu, B Wan, A Entezari, J Fang, Y Xu, Q Li | 2024 | International Journal of … | Elsevier | 53 | 26.5 |
| 707 | [PDF][PDF] A State-of-the-Art Review on Machine Learning-Based Multiscale Modeling, Simulation, Homogenization and Design of Materials. | D Bishara, Y Xie, WK Liu, S Li | 2023 | Archives of computational methods … | researchgate.net | 172 | 57.333333333333336 |
| 708 | [HTML][HTML] Revolutionizing market surveillance: customer relationship management with machine learning | X Shi, Y Zhang, M Yu, L Zhang | 2024 | PeerJ Computer Science | peerj.com | 31 | 15.5 |
| 709 | Machine learning models to accelerate the design of polymeric long-acting injectables | P Bannigan, Z Bao, RJ Hickman, M Aldeghi… | 2023 | Nature … | nature.com | 159 | 53.0 |
| 710 | [HTML][HTML] Machine learning approaches in predicting allosteric sites | F Nerin | 2024 | Current Opinion in Structural Biology | Elsevier | 36 | 18.0 |
| 711 | Acoustic fish species identification using deep learning and machine learning algorithms: A systematic review | A Yassir, SJ Andaloussi, O Ouchetto, K Mamza… | 2023 | Fisheries … | Elsevier | 45 | 15.0 |
| 712 | A survey of bone abnormalities detection using machine learning algorithms | AMA Barhoom, MR Jubair… | 2023 | PROCEEDINGS OF THE … | pubs.aip.org | 45 | 15.0 |
| 713 | Harnessing machine learning to find synergistic combinations for FDA-approved cancer drugs | T Abd El | 2024 | Scientific reports | nature.com | 63 | 31.5 |
| 714 | Development and application of traditional Chinese medicine using AI machine learning and deep learning strategies | D Pan, Y Guo, Y Fan, H Wan | 2024 | The American Journal of Chinese … | World Scientific | 35 | 17.5 |
| 715 | [HTML][HTML] Application of machine learning in automatic image identification of insects-a review | Y Gao, X Xue, G Qin, K Li, J Liu, Y Zhang, X Li | 2024 | Ecological Informatics | Elsevier | 40 | 20.0 |
| 716 | Physics-informed machine learning for battery degradation diagnostics: A comparison of state-of-the-art methods | S Navidi, A Thelen, T Li, C Hu | 2024 | Energy Storage Materials | Elsevier | 48 | 24.0 |
| 717 | Data cleaning and machine learning: a systematic literature review | PO Côté, A Nikanjam, N Ahmed, D Humeniuk… | 2024 | Automated Software … | Springer | 90 | 45.0 |
| 718 | [HTML][HTML] How machine learning is used to study addiction in digital healthcare: A systematic review | B Chhetri, LM Goyal, M Mittal | 2023 | International Journal of Information … | Elsevier | 59 | 19.666666666666668 |
| 719 | Oil spill classification using Machine learning | KK Ravulakollu, R Dewan, K Verma… | 2024 | … on Computing for … | ieeexplore.ieee.org | 63 | 31.5 |
| 720 | [HTML][HTML] Machine learning approaches to predict compressive strength of fly ash-based geopolymer concrete: A comprehensive review | M Rathnayaka, D Karunasinghe, C Gunasekara… | 2024 | … and Building Materials | Elsevier | 88 | 44.0 |
| 721 | [HTML][HTML] Comparative study of machine learning methods and GR2M model for monthly runoff prediction | P Ditthakit, S Pinthong, N Salaeh, J Weekaew… | 2023 | Ain Shams Engineering … | Elsevier | 49 | 16.333333333333332 |
| 722 | The Role of AI and Machine Learning in Optimising Cloud Migration Processes. | G Simuni, A Atla | 2024 | … of Business Analytics & Intelligence (IJBAI … | search.ebscohost.com | 28 | 14.0 |
| 723 | Application of Deep Neural Networks and Machine Learning algorithms for diagnosis of Brain tumour | S Wani, S Ahuja, A Kumar | 2023 | 2023 International Conference on … | ieeexplore.ieee.org | 60 | 20.0 |
| 724 | " We Have No Idea How Models will Behave in Production until Production": How Engineers Operationalize Machine Learning | S Shankar, R Garcia, JM Hellerstein… | 2024 | Proceedings of the … | dl.acm.org | 30 | 15.0 |
| 725 | [HTML][HTML] Metaverse and healthcare: Machine learning-enabled digital twins of cancer | O Moztarzadeh, M Jamshidi, S Sargolzaei, A Jamshidi… | 2023 | Bioengineering | mdpi.com | 117 | 39.0 |
| 726 | How to dp-fy ml: A practical guide to machine learning with differential privacy | N Ponomareva, H Hazimeh, A Kurakin, Z Xu… | 2023 | Journal of Artificial … | jair.org | 278 | 92.66666666666667 |
| 727 | Comparing BERT against traditional machine learning models in text classification | EC Garrido | 2023 | Journal of … | ojs.bonviewpress.com | 125 | 41.666666666666664 |
| 728 | Investigation of emergency department abandonment rates using machine learning algorithms in a single centre study | MR Marino, TA Trunfio, AM Ponsiglione, F Amato… | 2024 | Scientific Reports | nature.com | 26 | 13.0 |
| 729 | Intelligent decision support systems in construction engineering: An artificial intelligence and machine learning approaches | A Waqar | 2024 | Expert Systems with Applications | Elsevier | 65 | 32.5 |
| 730 | Vaccine supply chain management: An intelligent system utilizing blockchain, IoT and machine learning | H Hu, J Xu, M Liu, MK Lim | 2023 | Journal of business research | Elsevier | 184 | 61.333333333333336 |
| 731 | Subtleties in the trainability of quantum machine learning models | S Thanasilp, S Wang, NA Nghiem, P Coles… | 2023 | Quantum Machine … | Springer | 105 | 35.0 |
| 732 | Application of machine learning in polymer additive manufacturing: A review | T Nasrin, F Pourkamali‐Anaraki… | 2024 | Journal of Polymer … | Wiley Online Library | 58 | 29.0 |
| 733 | A mechanistic review on machine learning-supported detection and analysis of volatile organic compounds for food quality and safety | Y Feng, Y Wang, B Beykal, M Qiao, Z Xiao… | 2024 | Trends in Food Science & … | Elsevier | 63 | 31.5 |
| 734 | [HTML][HTML] Customer churning analysis using machine learning algorithms | B Prabadevi, R Shalini, BR Kavitha | 2023 | International Journal of Intelligent … | Elsevier | 90 | 30.0 |
| 735 | Machine learning for diagnosis of myocardial infarction using cardiac troponin concentrations | D Doudesis, KK Lee, J Boeddinghaus, A Bularga… | 2023 | Nature Medicine | nature.com | 120 | 40.0 |
| 736 | Machine learning with computer networks: techniques, datasets, and models | H Afifi, S Pochaba, A Boltres, D Laniewski… | 2024 | IEEE … | ieeexplore.ieee.org | 24 | 12.0 |
| 737 | Artificial intelligence based models to support water quality prediction using machine learning approach | P William, OJ Oyebode, G Ramu… | 2023 | … on Circuit Power … | ieeexplore.ieee.org | 99 | 33.0 |
| 738 | Machine learning-based time series models for effective CO2 emission prediction in India | S Kumari, SK Singh | 2023 | Environmental Science and Pollution Research | Springer | 176 | 58.666666666666664 |
| 739 | Machine learning-based predictive modelling for the enhancement of wine quality | K Jain, K Kaushik, SK Gupta, S Mahajan, S Kadry | 2023 | Scientific Reports | nature.com | 58 | 19.333333333333332 |
| 740 | Convergence of evolving artificial intelligence and machine learning techniques in precision oncology | E Fountzilas, T Pearce, MA Baysal, A Chakraborty… | 2025 | NPJ Digital … | nature.com | 58 | 58.0 |
| 741 | Web application based Diabetes prediction using Machine Learning | GR Kumar, RV Reddy, N Pughazendi… | 2023 | … on Advances in … | ieeexplore.ieee.org | 56 | 18.666666666666668 |
| 742 | Stability of clinical prediction models developed using statistical or machine learning methods | RD Riley, GS Collins | 2023 | Biometrical Journal | Wiley Online Library | 114 | 38.0 |
| 743 | [HTML][HTML] Recent advancements in computational drug design algorithms through machine learning and optimization | S Choudhuri, M Yendluri, S Poddar, A Li… | 2023 | Kinases and … | mdpi.com | 52 | 17.333333333333332 |
| 744 | [HTML][HTML] Evaluation of machine learning algorithms for malware detection | MS Akhtar, T Feng | 2023 | Sensors | mdpi.com | 68 | 22.666666666666668 |
| 745 | [HTML][HTML] A comprehensive survey of machine learning techniques and models for object detection | M Trigka, E Dritsas | 2025 | Sensors | mdpi.com | 25 | 25.0 |
| 746 | Machine-learning the skill of mutual fund managers | R Kaniel, Z Lin, M Pelger… | 2023 | Journal of Financial … | Elsevier | 120 | 40.0 |
| 747 | [HTML][HTML] Applications of machine learning in antibody discovery, process development, manufacturing and formulation: Current trends, challenges, and opportunities | TT Khuat, R Bassett, E Otte, A Grevis | 2024 | Computers & Chemical … | Elsevier | 49 | 24.5 |
| 748 | Structural Health Monitoring for impact localisation via machine learning | F Dipietrangelo, F Nicassio, G Scarselli | 2023 | Mechanical Systems and Signal … | Elsevier | 67 | 22.333333333333332 |
| 749 | [HTML][HTML] Explainable AI for machine fault diagnosis: understanding features' contribution in machine learning models for industrial condition monitoring | E Brusa, L Cibrario, C Delprete, LG Di Maggio | 2023 | Applied Sciences | mdpi.com | 109 | 36.333333333333336 |
| 750 | [PDF][PDF] Analyzing socio-academic factors and predictive modeling of student performance using machine learning techniques | R Al | 2024 | Emerg Sci J | researchgate.net | 29 | 14.5 |
| 751 | Machine learning-based seismic response and performance assessment of reinforced concrete buildings | F Kazemi, N Asgarkhani, R Jankowski | 2023 | Archives of Civil and Mechanical … | Springer | 182 | 60.666666666666664 |
| 752 | Triboelectric nanogenerators with machine learning for internet of things | J Yang, K Hong, Y Hao, X Zhu, Y Qin… | 2025 | Advanced Materials … | Wiley Online Library | 30 | 30.0 |
| 753 | Machine learning in chemical engineering: Hands-on activities | V Lavor, F de Come, MT dos Santos… | 2024 | Education for Chemical … | Elsevier | 26 | 13.0 |
| 754 | A comprehensive review for chronic disease prediction using machine learning algorithms | R Islam, A Sultana, MR Islam | 2024 | Journal of Electrical Systems and … | Springer | 36 | 18.0 |
| 755 | Return to tradition: Learning reliable heuristics with classical machine learning | DZ Chen, F Trevizan, S Thiébaux | 2024 | Proceedings of the International … | ojs.aaai.org | 28 | 14.0 |
| 756 | Machine learning in healthcare analytics: a state-of-the-art review | S Das, SP Nayak, B Sahoo, SC Nayak | 2024 | Archives of Computational … | Springer | 36 | 18.0 |
| 757 | [PDF][PDF] A study on the application of machine learning and deep learning techniques for skin cancer detection | H Ghosh, IS Rahat, SN Mohanty… | 2024 | … Journal of Computer … | researchgate.net | 70 | 35.0 |
| 758 | [PDF][PDF] Anomaly detection in cloud networks using machine learning algorithms | VR Gudelli | 2024 | African Journal of Artificial Intelligence and … | researchgate.net | 33 | 16.5 |
| 759 | Application of machine learning in predicting survival outcomes involving real-world data: a scoping review | Y Huang, J Li, M Li, RR Aparasu | 2023 | BMC medical research methodology | Springer | 72 | 24.0 |
| 760 | Machine learning-driven Internet of Things (MLIoT)-based healthcare monitoring system | KSL Kazi, MA Mahant | 2025 | igi | global.com | 32 | 32.0 |
| 761 | [HTML][HTML] Machine learning aided nanoindentation: A review of the current state and future perspectives | ES Puchi | 2023 | Current Opinion in Solid … | Elsevier | 51 | 17.0 |
| 762 | Machine learning in laboratory medicine: recommendations of the IFCC working group | SR Master, TC Badrick, A Bietenbeck… | 2023 | Clinical … | academic.oup.com | 44 | 14.666666666666666 |
| 763 | Classic machine learning methods | J Faouzi, O Colliot | 2023 | Machine learning for brain disorders | Springer | 31 | 10.333333333333334 |
| 764 | Conventional machine learning and deep learning in Alzheimer's disease diagnosis using neuroimaging: A review | Z Zhao, JH Chuah, KW Lai, CO Chow… | 2023 | Frontiers in … | frontiersin.org | 117 | 39.0 |
| 765 | Machine learning-assisted optical nano-sensor arrays in microorganism analysis | J Yang, S Lu, B Chen, F Hu, C Li, C Guo | 2023 | TrAC Trends in Analytical … | Elsevier | 62 | 20.666666666666668 |
| 766 | IoT driven by machine learning (MLIoT) for the retail apparel sector | KSL Kazi | 2024 | igi | global.com | 44 | 22.0 |
| 767 | Statistical, machine learning and deep learning forecasting methods: Comparisons and ways forward | S Makridakis, E Spiliotis… | 2023 | Journal of the … | Taylor & Francis | 137 | 45.666666666666664 |
| 768 | Enhancing cloud-based machine learning models with federated learning techniques | R Shamim, Y Farhaoui | 2023 | … Conference on Artificial Intelligence and Smart … | Springer | 50 | 16.666666666666668 |
| 769 | Machine learning for fault analysis in rotating machinery: A comprehensive review | O Das, DB Das, D Birant | 2023 | Heliyon | cell.com | 75 | 25.0 |
| 770 | Transparency of artificial intelligence/machine learning-enabled medical devices | AA Shick, CM Webber, N Kiarashi, JP Weinberg… | 2024 | NPJ Digital … | nature.com | 39 | 19.5 |
| 771 | [BOOK][B] Computational formalism: Art history and machine learning | A Wasielewski | 2023 | 2023 | books.google.com | 52 | 17.333333333333332 |
| 772 | A general framework of high-performance machine learning algorithms: application in structural mechanics | G Markou, NP Bakas, SA Chatzichristofis… | 2024 | Computational … | Springer | 34 | 17.0 |
| 773 | [HTML][HTML] A comprehensive review of machine learning for water quality prediction over the past five years | X Yan, T Zhang, W Du, Q Meng, X Xu… | 2024 | Journal of Marine Science … | mdpi.com | 54 | 27.0 |
| 774 | [HTML][HTML] Modeling the mechanical properties of recycled aggregate concrete using hybrid machine learning algorithms | Y Peng, C Unluer | 2023 | Resources | Elsevier | 119 | 39.666666666666664 |
| 775 | Comparative analysis of machine learning and deep learning models for improved cancer detection: A comprehensive review of recent advancements in diagnostic … | HM Rai, J Yoo, A Razaque | 2024 | Expert Systems with Applications | Elsevier | 33 | 16.5 |
| 776 | [HTML][HTML] A review of embedded machine learning based on hardware, application, and sensing scheme | A Biglari, W Tang | 2023 | Sensors | mdpi.com | 68 | 22.666666666666668 |
| 777 | [HTML][HTML] Ransomware detection using machine learning: A survey | A Alraizza, A Algarni | 2023 | Big Data and Cognitive Computing | mdpi.com | 100 | 33.333333333333336 |
| 778 | Sentiment analysis using Twitter data: a comparative application of lexicon-and machine-learning-based approach | Y Qi, Z Shabrina | 2023 | Social network analysis and mining | Springer | 200 | 66.66666666666667 |
| 779 | Testing the predictive power of reverse screening to infer drug targets, with the help of machine learning | A Daina, V Zoete | 2024 | Communications chemistry | nature.com | 37 | 18.5 |
| 780 | Advancements in machine learning and AI for intelligent systems in drone applications for smart city developments | S Boopathi | 2024 | igi | global.com | 44 | 22.0 |
| 781 | Smarter Systems: Applying Machine Learning to Complex, Real-Time Problem Solving | AS Shethiya | 2024 | Integrated Journal of Science and Technology | ijstpublication.com | 29 | 14.5 |
| 782 | Exploiting symmetry in variational quantum machine learning | JJ Meyer, M Mularski, E Gil | 2023 | PRX quantum | APS | 220 | 73.33333333333333 |
| 783 | A comprehensive survey for IoT security datasets taxonomy, classification and machine learning mechanisms | C Alex, G Creado, W Almobaideen, OA Alghanam… | 2023 | Computers & … | Elsevier | 62 | 20.666666666666668 |
| 784 | Sentiment analysis in multilingual context: Comparative analysis of machine learning and hybrid deep learning models | RK Das, M Islam, MM Hasan, S Razia, M Hassan… | 2023 | Heliyon | cell.com | 61 | 20.333333333333332 |
| 785 | Machine learning-assisted source tracing in domestic-industrial wastewater: A fluorescence information-based approach | Y Shu, F Kong, Y He, L Chen, H Liu, F Zan, X Lu, T Wu… | 2025 | Water Research | Elsevier | 24 | 24.0 |
| 786 | Towards quantum enhanced adversarial robustness in machine learning | MT West, SL Tsang, JS Low, CD Hill, C Leckie… | 2023 | Nature Machine … | nature.com | 73 | 24.333333333333332 |
| 787 | Machine learning approach using artificial neural networks to detect malicious nodes in IoT networks | KKS Liyakat | 2023 | International Conference on Machine Learning | Springer | 88 | 29.333333333333332 |
| 788 | Performance and early drop prediction for higher education students using machine learning | V Christou, I Tsoulos, V Loupas, AT Tzallas… | 2023 | Expert Systems with … | Elsevier | 37 | 12.333333333333334 |
| 789 | Medical informed machine learning: A scoping review and future research directions | F Leiser, S Rank, M Schmidt | 2023 | Artificial Intelligence in … | Elsevier | 23 | 7.666666666666667 |
| 790 | [PDF][PDF] Enhancing cyber security through artificial intelligence and machine learning: a literature review | C Merlano | 2024 | Journal of Cybersecurity | researchgate.net | 27 | 13.5 |
| 791 | Machine learning techniques for emotion detection and sentiment analysis: current state, challenges, and future directions | A Alslaity, R Orji | 2024 | Behaviour & Information Technology | Taylor & Francis | 143 | 71.5 |
| 792 | [BOOK][B] Advanced machine learning algorithms for complex financial applications | M Irfan, M Elhoseny, S Kassim, N Metawa | 2023 | 2023 | books.google.com | 65 | 21.666666666666668 |
| 793 | Prediction and diagnosis of depression using machine learning with electronic health records data: a systematic review | D Nickson, C Meyer, L Walasek, C Toro | 2023 | BMC medical informatics and … | Springer | 54 | 18.0 |
| 794 | AI-Powered Diagnosis: A Machine Learning Approach to Early Detection of Breast Cancer | H Tanveer, M Faheem, AH Khan… | 2025 | INTERNATIONAL … | rjwave.org | 50 | 50.0 |
| 795 | [HTML][HTML] Reducing literature screening workload with machine learning | T Burgard, A Bittermann | 2023 | Zeitschrift für Psychologie | econtent.hogrefe.com | 46 | 15.333333333333334 |
| 796 | An adversarial training framework for mitigating algorithmic biases in clinical machine learning | J Yang, AAS Soltan, DW Eyre, Y Yang… | 2023 | NPJ digital medicine | nature.com | 123 | 41.0 |
| 797 | TRIPOD+ AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods | GS Collins, KGM Moons, P Dhiman, RD Riley… | 2024 | bmj | bmj.com | 1061 | 530.5 |
| 798 | [HTML][HTML] The innovation effect of administrative hierarchy on intercity connection: The machine learning of twin cities | J Luo, Y Wang, G Li | 2023 | Journal of Innovation & Knowledge | Elsevier | 106 | 35.333333333333336 |
| 799 | Using machine learning techniques to forecast Mehram company's sales: A case study | M Soltaninejad, R Aghazadeh… | 2024 | Journal of Business … | search.proquest.com | 21 | 10.5 |
| 800 | Machine learning for analysis of experimental scattering and spectroscopy data in materials chemistry | AS Anker, KT Butler, R Selvan, KMØ Jensen | 2023 | Chemical Science | pubs.rsc.org | 37 | 12.333333333333334 |
| 801 | Online bearing fault diagnosis using numerical simulation models and machine learning classifications | H Wang, J Zheng, J Xiang | 2023 | Reliability Engineering & System Safety | Elsevier | 111 | 37.0 |
| 802 | [HTML][HTML] Application of machine learning initiatives and intelligent perspectives for CO2 emissions reduction in construction | L Farahzadi, M Kioumarsi | 2023 | Journal of Cleaner Production | Elsevier | 98 | 32.666666666666664 |
| 803 | [HTML][HTML] Towards a machine learning-based framework for DDOS attack detection in software-defined IoT (SD-IoT) networks | J Bhayo, SA Shah, S Hameed, A Ahmed, J Nasir… | 2023 | … Applications of Artificial … | Elsevier | 196 | 65.33333333333333 |
| 804 | [HTML][HTML] Utilizing machine learning on freight transportation and logistics applications: A review | K Tsolaki, T Vafeiadis, A Nizamis, D Ioannidis… | 2023 | ICT Express | Elsevier | 139 | 46.333333333333336 |
| 805 | [HTML][HTML] Machine learning approaches for predictions of CO2 emissions in the building sector | S Giannelos, F Bellizio, G Strbac, T Zhang | 2024 | Electric Power Systems … | Elsevier | 60 | 30.0 |
| 806 | Fuzzy machine learning logic utilization on hormonal imbalance dataset | R Khushal, U Fatima | 2024 | Computers in Biology and Medicine | Elsevier | 22 | 11.0 |
| 807 | Artificial intelligence (AI) and machine learning (ML) based decision support systems in mental health: An integrative review | O Higgins, BL Short, SK Chalup… | 2023 | International Journal of … | Wiley Online Library | 147 | 49.0 |
| 808 | A benchmark dataset for machine learning in ecotoxicology | C Schür, L Gasser, F Perez | 2023 | Scientific Data | nature.com | 38 | 12.666666666666666 |
| 809 | Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review | S Cheng, C Quilodrán | 2023 | IEEE/CAA Journal of … | ieeexplore.ieee.org | 242 | 80.66666666666667 |
| 810 | A Novel Approach to Human Iris Recognition And Verification Framework Using Machine Learning Algorithm | S Davuluri, S Kilaru, V Boppana… | 2023 | … and Informatics (IC3I … | ieeexplore.ieee.org | 56 | 18.666666666666668 |
| 811 | Forex market forecasting using machine learning: Systematic Literature Review and meta-analysis | M Ayitey Junior, P Appiahene, O Appiah, CN Bombie | 2023 | Journal of Big Data | Springer | 95 | 31.666666666666668 |
| 812 | Clinical trials are becoming more complex: a machine learning analysis of data from over 16,000 trials | N Markey, B Howitt, I El | 2024 | Scientific Reports | nature.com | 38 | 19.0 |
| 813 | Faults detection and diagnosis of PV systems based on machine learning approach using random forest classifier | AF Amiri, H Oudira, A Chouder, S Kichou | 2024 | Energy Conversion and … | Elsevier | 139 | 69.5 |
| 814 | Interpretable and explainable machine learning: A methods‐centric overview with concrete examples | R Marcinkevičs, JE Vogt | 2023 | Wiley Interdisciplinary Reviews: Data … | Wiley Online Library | 145 | 48.333333333333336 |
| 815 | [HTML][HTML] Application of machine learning modeling in prediction of solar still performance: a comprehensive survey | AS Abdullah, A Joseph, AW Kandeal, WH Alawee… | 2024 | Results in … | Elsevier | 60 | 30.0 |
| 816 | [HTML][HTML] Enhancing supply chain agility and sustainability through machine learning: Optimization techniques for logistics and inventory management | V Pasupuleti, B Thuraka, CS Kodete, S Malisetty | 2024 | Logistics | mdpi.com | 210 | 105.0 |
| 817 | [BOOK][B] Applications of machine learning and deep learning on biological data | F Masoodi, M Quasim, S Bukhari, S Dixit, S Alam | 2023 | 2023 | books.google.com | 39 | 13.0 |
| 818 | Prognosis of cervical cancer disease by applying machine learning techniques | G Kumawat, SK Vishwakarma… | 2023 | Journal of circuits … | World Scientific | 79 | 26.333333333333332 |
| 819 | [PDF][PDF] Adaptive machine learning models: Concepts for real-time financial fraud prevention in dynamic environments | HO Bello, AB Ige, MN Ameyaw | 2024 | World Journal of Advanced … | researchgate.net | 141 | 70.5 |
| 820 | Classification and diagnostic prediction of breast cancer metastasis on clinical data using machine learning algorithms | M Botlagunta, MD Botlagunta, MB Myneni… | 2023 | Scientific Reports | nature.com | 181 | 60.333333333333336 |
| 821 | [HTML][HTML] Developing a novel tool for assessing the groundwater incorporating water quality index and machine learning approach | AM Sajib, MTM Diganta, A Rahman… | 2023 | Groundwater for … | Elsevier | 88 | 29.333333333333332 |
| 822 | Exploring new depths: Applying machine learning for the analysis of student argumentation in chemistry | PP Martin, D Kranz, P Wulff… | 2024 | Journal of Research in … | Wiley Online Library | 38 | 19.0 |
| 823 | A bibliographic analysis of optimization of hydrogen production via electrochemical method using machine learning | S Iqbal, K Aftab, F tul Jannat, MA Baig, U Kalsoom | 2024 | Fuel | Elsevier | 19 | 9.5 |
| 824 | State-of-the-art review of machine learning and optimization algorithms applications in environmental effects of blasting | J Zhou, Y Zhang, Y Qiu | 2024 | Artificial Intelligence Review | Springer | 39 | 19.5 |
| 825 | Machine learning for service migration: A survey | N Toumi, M Bagaa, A Ksentini | 2023 | IEEE Communications Surveys … | ieeexplore.ieee.org | 26 | 8.666666666666666 |
| 826 | [HTML][HTML] Recent advances in machine-learning-based chemoinformatics: a comprehensive review | SK Niazi, Z Mariam | 2023 | International Journal of Molecular Sciences | mdpi.com | 90 | 30.0 |
| 827 | Machine learning applied to electronic health record data in home healthcare: a scoping review | M Hobensack, J Song, D Scharp, KH Bowles… | 2023 | International Journal of … | Elsevier | 52 | 17.333333333333332 |
| 828 | A practical guide to machine-learning scoring for structure-based virtual screening | VK Tran | 2023 | Nature Protocols | nature.com | 63 | 21.0 |
| 829 | A novel machine learning approach for solar radiation estimation | H Hissou, S Benkirane, A Guezzaz, M Azrour… | 2023 | Sustainability | mdpi.com | 61 | 20.333333333333332 |
| 830 | Comprehensive evaluation and performance analysis of machine learning in heart disease prediction | HA Al | 2024 | Scientific Reports | nature.com | 49 | 24.5 |
| 831 | Machine learning in tissue engineering | JL Guo, M Januszyk, MT Longaker | 2023 | Tissue Engineering Part A | liebertpub.com | 44 | 14.666666666666666 |
| 832 | Multi-dimensional discrimination in law and machine learning-A comparative overview | A Roy, J Horstmann, E Ntoutsi | 2023 | … of the 2023 ACM Conference on … | dl.acm.org | 27 | 9.0 |
| 833 | Analyzing breast cancer detection using machine learning & deep learning techniques | A Fatima, A Shabbir, JI Janjua, SA Ramay… | 2024 | Journal of Computing & … | jcbi.org | 22 | 11.0 |
| 834 | Roadmap for the use of machine learning and artificial intelligence in sensing | JF Masson | 2024 | ACS sensors | ACS Publications | 16 | 8.0 |
| 835 | Explanatory predictive model for COVID-19 severity risk employing machine learning, shapley addition, and LIME | M Laatifi, S Douzi, H Ezzine, CE Asry, A Naya… | 2023 | Scientific Reports | nature.com | 43 | 14.333333333333334 |
| 836 | [HTML][HTML] Modeling and optimization of renewable hydrogen systems: A systematic methodological review and machine learning integration | MD Mukelabai, ER Barbour, RE Blanchard | 2024 | Energy and AI | Elsevier | 31 | 15.5 |
| 837 | Applying machine learning to develop energy benchmarking for university buildings in Brazil | TC Quevedo, MS Geraldi, AP Melo | 2023 | Journal of building engineering | Elsevier | 49 | 16.333333333333332 |
| 838 | Machine learning for predicting survival of colorectal cancer patients | L Buk Cardoso, V Cunha Parro, S Verzinhasse Peres… | 2023 | Scientific reports | nature.com | 45 | 15.0 |
| 839 | [HTML][HTML] A decision support system for crop recommendation using machine learning classification algorithms | MK Senapaty, A Ray, N Padhy | 2024 | Agriculture | mdpi.com | 48 | 24.0 |
| 840 | [HTML][HTML] Do all roads lead to Rome? Studying distance measures in the context of machine learning | E Blanco | 2023 | Pattern Recognition | Elsevier | 27 | 9.0 |
| 841 | [HTML][HTML] Machine learning for multimodal mental health detection: a systematic review of passive sensing approaches | LS Khoo, MK Lim, CY Chong, R McNaney | 2024 | Sensors | mdpi.com | 75 | 37.5 |
| 842 | Puma optimizer (PO): a novel metaheuristic optimization algorithm and its application in machine learning | B Abdollahzadeh, N Khodadadi, S Barshandeh… | 2024 | Cluster … | Springer | 634 | 317.0 |
| 843 | Accurate global machine learning force fields for molecules with hundreds of atoms | S Chmiela, V Vassilev | 2023 | Science … | science.org | 206 | 68.66666666666667 |
| 844 | Intrusion detection system based on machine learning algorithms:(SVM and genetic algorithm) | A Alsajri, A Steiti | 2024 | Babylonian Journal of Machine Learning | mesopotamian.press | 39 | 19.5 |
| 845 | E-commerce fraud detection based on machine learning techniques: Systematic literature review | A Mutemi, F Bacao | 2024 | Big Data Mining and Analytics | ieeexplore.ieee.org | 74 | 37.0 |
| 846 | Crop mapping through a hybrid machine learning and deep learning method | B Asadi, A Shamsoddini | 2024 | Remote Sensing Applications: Society and … | Elsevier | 25 | 12.5 |
| 847 | Discovering biomarkers associated and predicting cardiovascular disease with high accuracy using a novel nexus of machine learning techniques for precision … | W DeGroat, H Abdelhalim, K Patel, D Mendhe… | 2024 | Scientific reports | nature.com | 237 | 118.5 |
| 848 | Past, present, and future of sustainable finance: insights from big data analytics through machine learning of scholarly research | S Kumar, D Sharma, S Rao, WM Lim… | 2025 | Annals of Operations … | Springer | 521 | 521.0 |
| 849 | Optimizing IoT intrusion detection system: feature selection versus feature extraction in machine learning | J Li, MS Othman, H Chen, LM Yusuf | 2024 | Journal of Big Data | Springer | 98 | 49.0 |
| 850 | [HTML][HTML] Estimation and prediction of the polymers' physical characteristics using the machine learning models | IP Malashin, VS Tynchenko, VA Nelyub, AS Borodulin… | 2023 | Polymers | mdpi.com | 46 | 15.333333333333334 |
| 851 | Machine learning-based intrusion detection system: an experimental comparison | I Hidayat, MZ Ali, A Arshad | 2023 | Journal of Computational and … | ojs.bonviewpress.com | 92 | 30.666666666666668 |
| 852 | Machine Learning: The Driving Force Behind Intelligent Systems and Predictive Analytics | D Virmani, MAS Ghori, N Tyagi… | 2024 | … on Trends in … | ieeexplore.ieee.org | 38 | 19.0 |
| 853 | [PDF][PDF] Predictive Analytics and Machine Learning in Direct Marketing for Anticipating Bank Term Deposit Subscriptions. | AM Zaki, N Khodadadi, W Hong Lim… | 2024 | American Journal of … | researchgate.net | 99 | 49.5 |
| 854 | [HTML][HTML] AIS data-driven ship trajectory prediction modelling and analysis based on machine learning and deep learning methods | H Li, H Jiao, Z Yang | 2023 | Transportation Research Part E: Logistics and … | Elsevier | 153 | 51.0 |
| 855 | Machine learning for sustainable organic waste treatment: a critical review | R Gupta, ZH Ouderji, Uzma, Z Yu, WT Sloan… | 2024 | NPJ Materials … | nature.com | 29 | 14.5 |
| 856 | Analysing the drivers of ecological footprint in Africa with machine learning algorithm | DK Espoir, R Sunge, T Nchofoung, AA Alola | 2024 | … Impact Assessment Review | Elsevier | 31 | 15.5 |
| 857 | Towards detection of network anomalies using machine learning algorithms on the NSL-KDD benchmark datasets | AD Vibhute, CH Patil, AV Mane, KV Kale | 2024 | Procedia Computer Science | Elsevier | 40 | 20.0 |
| 858 | A machine learning tutorial for operational meteorology. Part II: Neural networks and deep learning | RJ Chase, DR Harrison, GM Lackmann… | 2023 | Weather and … | journals.ametsoc.org | 42 | 14.0 |
| 859 | Challenges and limitations of synthetic minority oversampling techniques in machine learning | IM Alkhawaldeh, I Albalkhi… | 2023 | World journal of … | pmc.ncbi.nlm.nih.gov | 77 | 25.666666666666668 |
| 860 | Machine learning approaches to predict drug efficacy and toxicity in oncology | BA Badwan, G Liaropoulos, E Kyrodimos… | 2023 | Cell Reports … | cell.com | 72 | 24.0 |
| 861 | Machine learning WTI crude oil price predictions | B Jin, X Xu | 2025 | Journal of International Commerce | World Scientific | 29 | 29.0 |
| 862 | [HTML][HTML] Recent advances in data mining and machine learning for enhanced building energy management | X Zhou, H Du, S Xue, Z Ma | 2024 | Energy | Elsevier | 29 | 14.5 |
| 863 | Machine learning classifier algorithms for ransomware lockbit prediction | IMM El Emary, KA Yaghi | 2024 | bright | journal.org | 91 | 45.5 |
| 864 | Machine Learning Classification Algorithms for Accurate Breast Cancer Diagnosis | MS Alzboon, S Qawasmeh, M Alqaraleh… | 2023 | … on Emerging Smart … | ieeexplore.ieee.org | 32 | 10.666666666666666 |
| 865 | Temporal graph benchmark for machine learning on temporal graphs | S Huang, F Poursafaei, J Danovitch… | 2023 | Advances in … | proceedings.neurips.cc | 172 | 57.333333333333336 |
| 866 | A comparative study on the most effective machine learning model for blast loading prediction: From GBDT to Transformer | Q Li, Y Wang, Y Shao, L Li, H Hao | 2023 | Engineering Structures | Elsevier | 66 | 22.0 |
| 867 | Phishing detection system through hybrid machine learning based on URL | A Karim, M Shahroz, K Mustofa, SB Belhaouari… | 2023 | IEEE … | ieeexplore.ieee.org | 196 | 65.33333333333333 |
| 868 | [HTML][HTML] Optimization of mechanical properties of multiscale hybrid polymer nanocomposites: A combination of experimental and machine learning techniques | E Champa | 2024 | Composites Part B … | Elsevier | 77 | 38.5 |
| 869 | Machine learning system for indolence perception | SMU Sankar, NJ Kumar… | 2023 | … on Innovative Data … | ieeexplore.ieee.org | 32 | 10.666666666666666 |
| 870 | [HTML][HTML] Enhanced preprocessing approach using ensemble machine learning algorithms for detecting liver disease | AQ Md, S Kulkarni, CJ Joshua, T Vaichole, S Mohan… | 2023 | Biomedicines | mdpi.com | 108 | 36.0 |
| 871 | Interpretable machine learning assessment | H Han, Y Wu, J Wang, A Han | 2023 | Neurocomputing | Elsevier | 25 | 8.333333333333334 |
| 872 | Comparison of machine learning algorithms for slope stability prediction using an automated machine learning approach | TF Kurnaz, C Erden, U Dağdeviren, AS Demir… | 2024 | Natural Hazards | Springer | 34 | 17.0 |
| 873 | Applications of machine learning in thermochemical conversion of biomass-A review | SR Naqvi, Z Ullah, SAA Taqvi, MNA Khan, W Farooq… | 2023 | Fuel | Elsevier | 170 | 56.666666666666664 |
| 874 | [HTML][HTML] Exploring evaluation methods for interpretable machine learning: A survey | N Alangari, M El Bachir Menai, H Mathkour… | 2023 | Information | mdpi.com | 38 | 12.666666666666666 |
| 875 | [HTML][HTML] Creating rutting prediction models through machine learning techniques utilizing the long-term pavement performance database | AJ Alnaqbi, W Zeiada, GG Al | 2023 | Sustainability | mdpi.com | 50 | 16.666666666666668 |
| 876 | [HTML][HTML] Software defect prediction analysis using machine learning techniques | A Khalid, G Badshah, N Ayub, M Shiraz, M Ghouse | 2023 | Sustainability | mdpi.com | 91 | 30.333333333333332 |
| 877 | A review of recent advances, challenges, and opportunities in malicious insider threat detection using machine learning methods | FR Alzaabi, A Mehmood | 2024 | IEEE Access | ieeexplore.ieee.org | 132 | 66.0 |
| 878 | Divination of air quality assessment using ensembling machine learning approach | P William, DN Paithankar, PM Yawalkar… | 2023 | 2023 International … | ieeexplore.ieee.org | 53 | 17.666666666666668 |
| 879 | [HTML][HTML] Application of artificial intelligence and machine learning for BIM | D Bassir, H Lodge, H Chang, J Majak… | 2023 | International Journal for … | ijsmdo.org | 50 | 16.666666666666668 |
| 880 | Quantum machine learning for computational methods in engineering: a systematic review | SK Sood, M Agrewal | 2024 | Archives of Computational Methods in Engineering | Springer | 23 | 11.5 |
| 881 | Machine learning and power relations | J Maas | 2023 | AI & SOCIETY | Springer | 39 | 13.0 |
| 882 | Intrusion Detection System with Customized Machine Learning Techniques for NSL-KDD Dataset. | M Zakariah, SA AlQahtani… | 2023 | Computers … | search.ebscohost.com | 47 | 15.666666666666666 |
| 883 | [HTML][HTML] Adversarial machine learning attacks against intrusion detection systems: A survey on strategies and defense | A Alotaibi, MA Rassam | 2023 | Future Internet | mdpi.com | 141 | 47.0 |
| 884 | Cloud-based in-situ battery life prediction and classification using machine learning | Y Zhang, M Zhao | 2023 | Energy Storage Materials | Elsevier | 104 | 34.666666666666664 |
| 885 | Identification of 71 factors influencing urban vitality and examination of their spatial dependence: A comprehensive validation applying multiple machine-learning … | Z Wang, X Wang, Y Liu, L Zhu | 2024 | Sustainable Cities and Society | Elsevier | 35 | 17.5 |
| 886 | Practical machine learning: Forecasting daily financial markets directions | BM Henrique, VA Sobreiro, H Kimura | 2023 | Expert Systems with Applications | Elsevier | 26 | 8.666666666666666 |
| 887 | Rigor with machine learning from field theory to the Poincaré conjecture | S Gukov, J Halverson, F Ruehle | 2024 | Nature Reviews Physics | nature.com | 25 | 12.5 |
| 888 | Power system monitoring for electrical disturbances in wide network using machine learning | J Wei, A Chammam, J Feng, A Alshammari… | 2024 | … Informatics and Systems | Elsevier | 24 | 12.0 |
| 889 | A machine learning-based comparative approach to predict the crop yield using supervised learning with regression models | B Panigrahi, KCR Kathala, M Sujatha | 2023 | Procedia Computer Science | Elsevier | 107 | 35.666666666666664 |
| 890 | Direct generation of protein conformational ensembles via machine learning | G Janson, G Valdes | 2023 | Nature Communications | nature.com | 148 | 49.333333333333336 |
| 891 | Introduction of machine learning and artificial intelligence in biofuel technology | JA Okolie | 2024 | Current Opinion in Green and Sustainable Chemistry | Elsevier | 37 | 18.5 |
| 892 | Machine learning investigation of tuberculosis with medicine immunity impact | H Qureshi, Z Shah, MAZ Raja, MY Alshahrani… | 2024 | … and Infectious Disease | Elsevier | 26 | 13.0 |
| 893 | [HTML][HTML] Fuzzy machine learning applications in environmental engineering: Does the ability to deal with uncertainty really matter? | A Bressane, AJS Garcia, MV Castro, SD Xerfan… | 2024 | Sustainability | mdpi.com | 34 | 17.0 |
| 894 | [HTML][HTML] Advancing healthcare: synergizing biosensors and machine learning for early cancer diagnosis | M Kokabi, MN Tahir, D Singh, M Javanmard | 2023 | Biosensors | mdpi.com | 48 | 16.0 |
| 895 | Machine learning sensors | P Warden, M Stewart, B Plancher, S Katti… | 2023 | Communications of the … | dl.acm.org | 35 | 11.666666666666666 |
| 896 | [HTML][HTML] A comprehensive survey of unmanned aerial vehicles detection and classification using machine learning approach: Challenges, solutions, and future … | MH Rahman, MAS Sejan, MA Aziz, R Tabassum… | 2024 | Remote Sensing | mdpi.com | 64 | 32.0 |
| 897 | Machine learning and bias in medical imaging: opportunities and challenges | A Vrudhula, AC Kwan, D Ouyang… | 2024 | Circulation … | ahajournals.org | 32 | 16.0 |
| 898 | Applications of artificial intelligence, machine learning, and deep learning on facial plastic surgeries | E Tokgöz, MA Carro | 2023 | Cosmetic and reconstructive facial plastic surgery: A … | Springer | 49 | 16.333333333333332 |
| 899 | Machine Learning Based Cardiovascular Detection Approach | RK Kanna, A Ambikapathy, M Brayyich… | 2023 | 2023 10th IEEE Uttar … | ieeexplore.ieee.org | 27 | 9.0 |
| 900 | [BOOK][B] AI and machine learning impacts in intelligent supply chain | BK Pandey, UK Kanike, AS George, D Pandey | 2024 | 2024 | books.google.com | 32 | 16.0 |
| 901 | [HTML][HTML] Optimisation of knowledge management (KM) with machine learning (ML) enabled | M Anshari, M Syafrudin, A Tan, NL Fitriyani, Y Alas | 2023 | Information | mdpi.com | 51 | 17.0 |
| 902 | Regional steel price index predictions for the southwest Chinese market through machine learning | B Jin, X Xu | 2024 | Ironmaking & Steelmaking | journals.sagepub.com | 22 | 11.0 |
| 903 | Towards data-centric graph machine learning: Review and outlook | X Zheng, Y Liu, Z Bao, M Fang, X Hu, AWC Liew… | 2023 | arXiv preprint arXiv … | arxiv.org | 39 | 13.0 |
| 904 | Using supervised machine learning for large‐scale classification in management research: The case for identifying artificial intelligence patents | M Miric, N Jia, KG Huang | 2023 | Strategic Management Journal | Wiley Online Library | 164 | 54.666666666666664 |
| 905 | Prediction of Alzheimer's disease using hybrid machine learning technique | MS Kumar, H Azath, AK Velmurugan… | 2023 | AIP Conference … | pubs.aip.org | 67 | 22.333333333333332 |
| 906 | A review of axial and radial ejectors: Geometric design, computational analysis, performance, and machine learning approaches | G Al | 2025 | Applied Thermal … | Elsevier | 10 | 10.0 |
| 907 | [HTML][HTML] The personal health applications of machine learning techniques in the internet of behaviors | Z Amiri, A Heidari, M Darbandi, Y Yazdani… | 2023 | Sustainability | mdpi.com | 91 | 30.333333333333332 |
| 908 | A comprehensive survey on machine learning approaches for fake news detection | J Alghamdi, S Luo, Y Lin | 2024 | Multimedia Tools and Applications | Springer | 85 | 42.5 |
| 909 | Machine learning in toxicological sciences: opportunities for assessing drug toxicity | L Tonoyan, AG Siraki | 2024 | Frontiers in Drug Discovery | frontiersin.org | 23 | 11.5 |
| 910 | Accelerating ionizable lipid discovery for mRNA delivery using machine learning and combinatorial chemistry | B Li, IO Raji, AGR Gordon, L Sun, TM Raimondo… | 2024 | Nature Materials | nature.com | 103 | 51.5 |
| 911 | Application of machine learning in carbon capture and storage: An in-depth insight from the perspective of geoscience | P Yao, Z Yu, Y Zhang, T Xu | 2023 | Fuel | Elsevier | 117 | 39.0 |
| 912 | Coronary heart disease prediction and classification using hybrid machine learning algorithms | KB Sk, D Roja, SS Priya, L Dalavi… | 2023 | … on Innovative Data … | ieeexplore.ieee.org | 102 | 34.0 |
| 913 | [HTML][HTML] Pipeline leakage detection using acoustic emission and machine learning algorithms | N Ullah, Z Ahmed, JM Kim | 2023 | Sensors | mdpi.com | 98 | 32.666666666666664 |
| 914 | Identification of heart diseases using novel machine learning method | R Veeranjaneyulu, S Boopathi… | 2023 | … on Advances in … | ieeexplore.ieee.org | 46 | 15.333333333333334 |
| 915 | Addressing uncertainty in the safety assurance of machine-learning | S Burton, B Herd | 2023 | Frontiers in Computer Science | frontiersin.org | 43 | 14.333333333333334 |
| 916 | [HTML][HTML] Detecting anomalies in blockchain transactions using machine learning classifiers and explainability analysis | M Hasan, MS Rahman, H Janicke, IH Sarker | 2024 | Blockchain: Research and … | Elsevier | 44 | 22.0 |
| 917 | [HTML][HTML] Analysis of bitcoin price prediction using machine learning | J Chen | 2023 | Journal of risk and financial management | mdpi.com | 156 | 52.0 |
| 918 | Breast cancer prediction based on multiple machine learning algorithms | S Zhou, C Hu, S Wei, X Yan | 2024 | Technology in cancer research … | journals.sagepub.com | 24 | 12.0 |
| 919 | [HTML][HTML] Machine learning models for the identification of prognostic and predictive cancer biomarkers: a systematic review | Q Al | 2023 | International journal of … | mdpi.com | 117 | 39.0 |
| 920 | Application of machine learning in measurement of ageing and geriatric diseases: a systematic review | A Das, P Dhillon | 2023 | BMC geriatrics | Springer | 26 | 8.666666666666666 |
| 921 | Credit risk prediction using ensemble machine learning algorithms | V Kanaparthi | 2023 | 2023 International Conference on Inventive … | ieeexplore.ieee.org | 42 | 14.0 |
| 922 | A comparative study of statistical and machine learning models on carbon dioxide emissions prediction of China | X Li, X Zhang | 2023 | Environmental Science and Pollution Research | Springer | 62 | 20.666666666666668 |
| 923 | Enhancing collaborative machine learning for security and privacy in federated learning | M Zhu, J Yuan, G Wang, Z Xu… | 2024 | Journal of Theory and … | centuryscipub.com | 23 | 11.5 |
| 924 | Industrial carbon emission forecasting considering external factors based on linear and machine learning models | L Ye, P Du, S Wang | 2024 | Journal of Cleaner Production | Elsevier | 46 | 23.0 |
| 925 | Smart food monitoring system based on iot and machine learning | MJI Tutul, M Alam, MAH Wadud | 2023 | … | ieeexplore.ieee.org | 31 | 10.333333333333334 |
| 926 | Calibrating machine learning approaches for probability estimation: A comprehensive comparison | FM Ojeda, ML Jansen, A Thiéry… | 2023 | Statistics in … | Wiley Online Library | 35 | 11.666666666666666 |
| 927 | Towards understanding fairness and its composition in ensemble machine learning | U Gohar, S Biswas, H Rajan | 2023 | 2023 IEEE/ACM 45th … | ieeexplore.ieee.org | 49 | 16.333333333333332 |
| 928 | Machine learning for administrative health records: A systematic review of techniques and applications | A Caruana, M Bandara, K Musial, D Catchpoole… | 2023 | Artificial intelligence in … | Elsevier | 23 | 7.666666666666667 |
| 929 | Machine learning-based optimal crop selection system in smart agriculture | S Rani, AK Mishra, A Kataria, S Mallik, H Qin | 2023 | Scientific Reports | nature.com | 126 | 42.0 |
| 930 | Forecasting realized volatility with machine learning: Panel data perspective | H Zhu, L Bai, L He, Z Liu | 2023 | Journal of Empirical Finance | Elsevier | 31 | 10.333333333333334 |
| 931 | [HTML][HTML] An inception V3 approach for malware classification using machine learning and transfer learning | M Ahmed, N Afreen, M Ahmed, M Sameer… | 2023 | International Journal of … | Elsevier | 105 | 35.0 |
| 932 | [HTML][HTML] … -efficient routing protocols for UWSNs: A comprehensive review of taxonomy, challenges, opportunities, future research directions, and machine learning … | SU Khan, ZU Khan, M Alkhowaiter, J Khan… | 2024 | Journal of King Saud … | Elsevier | 35 | 17.5 |
| 933 | Recent and upcoming developments in randomized numerical linear algebra for machine learning | M Dereziński, MW Mahoney | 2024 | Proceedings of the 30th ACM SIGKDD … | dl.acm.org | 18 | 9.0 |
| 934 | [BOOK][B] Fundamentals of supervised machine learning | G Cerulli | 2023 | 2023 | Springer | 28 | 9.333333333333334 |
| 935 | Machine learning in embedded systems: Limitations, solutions and future challenges | E Batzolis, E Vrochidou… | 2023 | 2023 IEEE 13th annual … | ieeexplore.ieee.org | 23 | 7.666666666666667 |
| 936 | Data-driven predictions of shield attitudes using Bayesian machine learning | L Wang, Q Pan, S Wang | 2024 | Computers and Geotechnics | Elsevier | 26 | 13.0 |
| 937 | [HTML][HTML] Slope stability prediction method based on intelligent optimization and machine learning algorithms | Y Yang, W Zhou, IM Jiskani, X Lu, Z Wang, B Luan | 2023 | Sustainability | mdpi.com | 45 | 15.0 |
| 938 | [HTML][HTML] A novel approach for estimating and predicting uncertainty in water quality index model using machine learning approaches | MG Uddin, S Nash, A Rahman, AI Olbert | 2023 | Water Research | Elsevier | 183 | 61.0 |
| 939 | Machine learning and IoT-based approach for tool condition monitoring: A review and future prospects | MQ Tran, HP Doan, VQ Vu, LT Vu | 2023 | Measurement | Elsevier | 124 | 41.333333333333336 |
| 940 | Efficient machine learning method for evaluating compressive strength of cement stabilized soft soil | C Zhang, Z Zhu, F Liu, Y Yang, Y Wan, W Huo… | 2023 | … and Building Materials | Elsevier | 59 | 19.666666666666668 |
| 941 | Machine learning reveals diverse cell death patterns in lung adenocarcinoma prognosis and therapy | S Wang, R Wang, D Hu, C Zhang, P Cao… | 2024 | NPJ Precision … | nature.com | 54 | 27.0 |
| 942 | Machine learning for membrane design in energy production, gas separation, and water treatment: a review | AI Osman, M Nasr, M Farghali, SS Bakr… | 2024 | Environmental … | Springer | 58 | 29.0 |
| 943 | [HTML][HTML] The application of machine learning to air pollution research: A bibliometric analysis | Y Li, Z Sha, A Tang, K Goulding, X Liu | 2023 | Ecotoxicology and Environmental … | Elsevier | 50 | 16.666666666666668 |
| 944 | Spice, a dataset of drug-like molecules and peptides for training machine learning potentials | P Eastman, PK Behara, DL Dotson, R Galvelis, JE Herr… | 2023 | Scientific Data | nature.com | 195 | 65.0 |
| 945 | Weisfeiler and leman go machine learning: The story so far | C Morris, Y Lipman, H Maron, B Rieck… | 2023 | … of Machine Learning … | jmlr.org | 169 | 56.333333333333336 |
| 946 | SNIB: improving spike-based machine learning using nonlinear information bottleneck | S Yang, B Chen | 2023 | IEEE transactions on systems | ieeexplore.ieee.org | 89 | 29.666666666666668 |
| 947 | Data-driven sustainability: leveraging big data and machine learning to build a greener future | MA Mohammed, MA Ahmed… | 2023 | Babylonian Journal of … | mesopotamian.press | 52 | 17.333333333333332 |
| 948 | Machine learning strategies for reaction development: toward the low-data limit | E Shim, A Tewari, T Cernak… | 2023 | Journal of chemical … | ACS Publications | 28 | 9.333333333333334 |
| 949 | Machine learning for large-scale optimization in 6G wireless networks | Y Shi, L Lian, Y Shi, Z Wang, Y Zhou… | 2023 | … Surveys & Tutorials | ieeexplore.ieee.org | 170 | 56.666666666666664 |
| 950 | The new era of computer network by using machine learning | S Namasudra, P Lorenz, U Ghosh | 2023 | Mobile Networks and Applications | Springer | 20 | 6.666666666666667 |
| 951 | [HTML][HTML] Application of machine learning for insect monitoring in grain facilities | QA Mendoza, L Pordesimo, M Neilsen, P Armstrong… | 2023 | AI | mdpi.com | 36 | 12.0 |
| 952 | Machine learning algorithms reveal potential miRNAs biomarkers in gastric cancer | H Azari, E Nazari, R Mohit, A Asadnia, M Maftooh… | 2023 | Scientific reports | nature.com | 44 | 14.666666666666666 |
| 953 | Pima Indians diabetes mellitus classification based on machine learning (ML) algorithms | V Chang, J Bailey, QA Xu, Z Sun | 2023 | Neural Computing and Applications | Springer | 350 | 116.66666666666667 |
| 954 | A systematic review of recent machine learning techniques for plant disease identification and classification | L Goel, J Nagpal | 2023 | IETE Technical Review | Taylor & Francis | 66 | 22.0 |
| 955 | Enhanced SOC estimation of lithium ion batteries with RealTime data using machine learning algorithms | PS Babu, IV, AB, VS, KC | 2024 | Scientific Reports | nature.com | 44 | 22.0 |
| 956 | A comparative analysis of machine learning algorithms for the purpose of predicting Norwegian air passenger traffic | A Stanulov, S Yassine | 2024 | … Journal of Mathematics | ijmscs.org | 58 | 29.0 |
| 957 | Identifying top ten predictors of type 2 diabetes through machine learning analysis of UK Biobank data | M Lugner, A Rawshani, E Helleryd, B Eliasson | 2024 | Scientific reports | nature.com | 46 | 23.0 |
| 958 | Machine learning insights in predicting heavy metals interaction with biochar | X Wei, Y Liu, L Shen, Z Lu, Y Ai, X Wang | 2024 | Biochar | Springer | 29 | 14.5 |
| 959 | Machine learning for coverage optimization in wireless sensor networks: a comprehensive review | OS Egwuche, A Singh, AE Ezugwu, J Greeff… | 2023 | Annals of Operations … | Springer | 47 | 15.666666666666666 |
| 960 | survex: an R package for explaining machine learning survival models | M Spytek, M Krzyziński, SH Langbein, H Baniecki… | 2023 | … | academic.oup.com | 30 | 10.0 |
| 961 | Exploring machine learning solutions for overcoming challenges in IoT-based wireless sensor network routing: a comprehensive review | R Priyadarshi | 2024 | Wireless Networks | Springer | 75 | 37.5 |
| 962 | Engagement assessment in project-based education: a machine learning approach in team chat analysis | S Farshad, E Zorin, N Amangeldiuly… | 2024 | Education and Information … | Springer | 34 | 17.0 |
| 963 | [PDF][PDF] Ransomware detection with machine learning by applying the lapranove function on bytecode | T Zhong, J Li | 2024 | 2024 | files.osf.io | 85 | 42.5 |
| 964 | [PDF][PDF] Leveraging machine learning to optimize renewable energy integration in developing economies | I Barrie, CP Agupugo, HO Iguare… | 2024 | Global Journal of … | researchgate.net | 31 | 15.5 |
| 965 | Bias in machine learning models can be significantly mitigated by careful training: Evidence from neuroimaging studies | R Wang, P Chaudhari, C Davatzikos | 2023 | Proceedings of the National … | pnas.org | 79 | 26.333333333333332 |
| 966 | [HTML][HTML] AutoML: A systematic review on automated machine learning with neural architecture search | I Salehin, MS Islam, P Saha, SM Noman, A Tuni… | 2024 | Journal of Information … | Elsevier | 194 | 97.0 |
| 967 | [PDF][PDF] An intelligent machine learning approach for fraud detection in medical claim insurance: A comprehensive study | S Agarwal | 2023 | Scholars Journal of Engineering and Technology | saspublishers.com | 55 | 18.333333333333332 |
| 968 | Machine learning for advancing low-temperature plasma modeling and simulation | J Trieschmann, L Vialetto… | 2023 | Journal of Micro … | spiedigitallibrary.org | 36 | 12.0 |
| 969 | Machine learning for urban heat island (UHI) analysis: Predicting land surface temperature (LST) in urban environments | G Tanoori, A Soltani, A Modiri | 2024 | Urban Climate | Elsevier | 93 | 46.5 |
| 970 | The impact of imputation quality on machine learning classifiers for datasets with missing values | T Shadbahr, M Roberts, J Stanczuk, J Gilbey… | 2023 | Communications … | nature.com | 83 | 27.666666666666668 |
| 971 | Machine learning prediction of the degree of food processing | G Menichetti, B Ravandi, D Mozaffarian… | 2023 | Nature … | nature.com | 123 | 41.0 |
| 972 | A novel approach utilizing machine learning for the early diagnosis of Alzheimer's disease | KMM Uddin, MJ Alam, MA Uddin, S Aryal | 2023 | Biomedical Materials & … | Springer | 82 | 27.333333333333332 |
| 973 | Current status and analysis of machine learning in hepatocellular carcinoma | S Feng, J Wang, L Wang, Q Qiu… | 2023 | Journal of clinical … | pmc.ncbi.nlm.nih.gov | 30 | 10.0 |
| 974 | Detecting insurance fraud using supervised and unsupervised machine learning | J Debener, V Heinke, J Kriebel | 2023 | Journal of Risk and Insurance | Wiley Online Library | 67 | 22.333333333333332 |
| 975 | Evaluation of machine learning algorithms for groundwater quality modeling | S Sahour, M Khanbeyki, V Gholami, H Sahour… | 2023 | … Science and Pollution … | Springer | 42 | 14.0 |
| 976 | Leveraging Temporal Patterns with LSTMs Networks for Financial Forecasting: A New Stastical Machine Learning Approach | K Thinakaran, S Soman, L Anitha… | 2023 | … Security and Artificial … | ieeexplore.ieee.org | 60 | 20.0 |
| 977 | Environmental sustainability: A machine learning approach for cost analysis in plastic recycling classification | B Carrera, JB Mata, VL Pinol, K Kim | 2023 | Resources | Elsevier | 34 | 11.333333333333334 |
| 978 | New era of artificial intelligence and machine learning-based detection, diagnosis, and therapeutics in Parkinson's disease | R Gupta, S Kumari, A Senapati, RK Ambasta… | 2023 | Ageing research … | Elsevier | 119 | 39.666666666666664 |
| 979 | Assessment of groundwater suitability for sustainable irrigation: a comprehensive study using indexical, statistical, and machine learning approaches | G Singh, J Singh, OA Wani, JC Egbueri… | 2024 | Groundwater for … | Elsevier | 72 | 36.0 |
| 980 | [HTML][HTML] Advances in hydrogen storage materials: harnessing innovative technology, from machine learning to computational chemistry, for energy storage solutions | AI Osman, M Nasr, AS Eltaweil, M Hosny… | 2024 | International journal of … | Elsevier | 131 | 65.5 |
| 981 | [PDF][PDF] Técnicas y aplicaciones del Machine Learning e Inteligencia Artificial en educación: una revisión sistemática | W Forero | 2024 | Revista Iberoamericana de … | redalyc.org | 165 | 82.5 |
| 982 | Penggunaan Python sebagai bahasa pemrograman untuk machine learning dan deep learning | MRS Alfarizi, MZ Al | 2023 | Karimah … | ojs.unida.ac.id | 121 | 40.333333333333336 |
| 983 | [CITATION][C] Pembelajaran Machine Learning | A Wijoyo, AY Saputra, S Ristanti, S Sya'ban, M Amalia… | 2024 | A Wijoyo | … Ilmu Komput. dan Sci., vol. 3 …, 2024 | 34 | 17.0 |
| 984 | Penerapan machine learning dalam prediksi tingkat kasus penyakit di Indonesia | RG Wardhana, G Wang… | 2023 | Journal of Information … | devjurnal.amikom.ac.id | 49 | 16.333333333333332 |
| 985 | [CITATION][C] Perbandingan Algoritma Machine Learning untuk Analisis Sentimen Berbasis Aspek pada Review Female Daily | MH Wicaksono, MD Purbolaksono, S Al Faraby | 2023 | MH Wicaksono | eProceedings of Engineering, 2023 | 307 | 102.33333333333333 |
| 986 | [CITATION][C] Prediksi hasil panen tanaman pangan sumatera dengan metode machine learning | A Satria, RM Badri, I Safitri, H Artikel | 2023 | A Satria | Digital Transformation Technology, 2023 | 30 | 10.0 |
| 987 | Enhancing financial fraud detection using adaptive machine learning models and business analytics | A Adewumi, SE Ewim, NJ Sam | 2024 | International Journal of … | elibrary.ru | 68 | 34.0 |