Seuraa
Matthew B. A. McDermott
Matthew B. A. McDermott
Postdoctoral Researcher, Harvard Medical School, Department of Biomedical Informatics
Vahvistettu sähköpostiosoite verkkotunnuksessa hms.harvard.edu
Nimike
Viittaukset
Viittaukset
Vuosi
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
21242019
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
3942021
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
2792020
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
2662019
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
228*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
2082020
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
179*2019
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
1662020
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
622019
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
602020
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
57*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
442018
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
342020
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
332021
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
322018
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
212012
Deep learning benchmarks on L1000 gene expression data
MBA McDermott, J Wang, WN Zhao, SD Sheridan, P Szolovits, I Kohane, ...
IEEE/ACM transactions on computational biology and bioinformatics 17 (6 …, 2019
192019
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
162020
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
15*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
152018
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Artikkelit 1–20