| Publicly available clinical BERT embeddings E Alsentzer, JR Murphy, W Boag, WH Weng, D Jin, T Naumann, ... Proceedings of the 2nd Clinical Natural Language Processing Workshop 2 (W19 …, 2019 | 1314 | 2019 |
| Clinically accurate chest x-ray report generation G Liu, TMH Hsu, M McDermott, W Boag, WH Weng, P Szolovits, ... Machine Learning for Healthcare Conference, 249-269, 2019 | 167 | 2019 |
| CheXclusion: Fairness gaps in deep chest X-ray classifiers L Seyyed-Kalantari, G Liu, M McDermott, IY Chen, M Ghassemi BIOCOMPUTING 2021: proceedings of the Pacific symposium, 232-243, 2020 | 158 | 2020 |
| Reproducibility in machine learning for health research: Still a ways to go MBA McDermott, S Wang, N Marinsek, R Ranganath, L Foschini, ... Science Translational Medicine 13 (586), eabb1655, 2021 | 135* | 2021 |
| Rethinking clinical prediction: why machine learning must consider year of care and feature aggregation B Nestor, M McDermott, G Chauhan, T Naumann, MC Hughes, ... Proceedings of the 4th Machine Learning for Healthcare Conference 106, 381-405, 2019 | 130* | 2019 |
| Underdiagnosis bias of artificial intelligence algorithms applied to chest radiographs in under-served patient populations L Seyyed-Kalantari, H Zhang, MBA McDermott, IY Chen, M Ghassemi Nature medicine 27 (12), 2176-2182, 2021 | 127 | 2021 |
| Mimic-extract: A data extraction, preprocessing, and representation pipeline for mimic-iii S Wang, MBA McDermott, G Chauhan, M Ghassemi, MC Hughes, ... Proceedings of the ACM conference on health, inference, and learning, 222-235, 2020 | 123 | 2020 |
| Hurtful words: quantifying biases in clinical contextual word embeddings H Zhang, AX Lu, M Abdalla, M McDermott, M Ghassemi proceedings of the ACM Conference on Health, Inference, and Learning, 110-120, 2020 | 107 | 2020 |
| Negative predictive value of surveillance PET/CT in head and neck squamous cell cancer M McDermott, M Hughes, T Rath, JT Johnson, DE Heron, GJ Kubicek, ... American Journal of Neuroradiology 34 (8), 1632-1636, 2013 | 68 | 2013 |
| Baselines for chest x-ray report generation W Boag, TMH Hsu, M McDermott, G Berner, E Alesentzer, P Szolovits Machine learning for health workshop, 126-140, 2020 | 45 | 2020 |
| Trends and focus of machine learning applications for health research B Beaulieu-Jones, SG Finlayson, C Chivers, I Chen, M McDermott, ... JAMA network open 2 (10), e1914051-e1914051, 2019 | 45 | 2019 |
| A comprehensive EHR timeseries pre-training benchmark M McDermott, B Nestor, E Kim, W Zhang, A Goldenberg, P Szolovits, ... Proceedings of the Conference on Health, Inference, and Learning, 257-278, 2021 | 31* | 2021 |
| Unsupervised multimodal representation learning across medical images and reports TMH Hsu, WH Weng, W Boag, M McDermott, P Szolovits arXiv preprint arXiv:1811.08615, 2018 | 31 | 2018 |
| Semi-supervised biomedical translation with cycle wasserstein regression GANs M McDermott, T Yan, T Naumann, N Hunt, HS Suresh, P Szolovits, ... AAAI Conference on Artificial Intelligence 32, 2363-2370, 2018 | 28 | 2018 |
| Chexpert++: Approximating the chexpert labeler for speed, differentiability, and probabilistic output MBA McDermott, TMH Hsu, WH Weng, M Ghassemi, P Szolovits Machine Learning for Healthcare Conference, 913-927, 2020 | 26 | 2020 |
| Modeling the role of negative cooperativity in metabolic regulation and homeostasis EC Bush, AE Clark, CM DeBoever, LE Haynes, S Hussain, S Ma, ... PloS one 7 (11), e48920, 2012 | 19 | 2012 |
| Meta-learning to improve pre-training A Raghu, J Lorraine, S Kornblith, M McDermott, DK Duvenaud Advances in Neural Information Processing Systems 34, 23231-23244, 2021 | 15 | 2021 |
| Machine learning for health (ML4H) 2020: Advancing healthcare for all SK Sarkar, S Roy, E Alsentzer, MBA McDermott, F Falck, I Bica, G Adams, ... Machine Learning for Health, 1-11, 2020 | 14 | 2020 |
| A Framework for Relation Extraction Across Multiple Datasets in Multiple Domains G Chauhan, M McDermott, P Szolovits Proceedings of the 2019 Workshop on Widening NLP, 18-20, 2019 | 13* | 2019 |
| MIT-MEDG at SemEval-2018 task 7: Semantic relation classification via convolution neural network D Jin, F Dernoncourt, E Sergeeva, M McDermott, G Chauhan Proceedings of the 12th international workshop on semantic evaluation, 798-804, 2018 | 13 | 2018 |
Dr. Marzyeh GhassemiAssistant Professor, EECS.CSAIL/IMES, MITVerified email at mit.edu
