Semi-Supervised Biomedical Translation With Cycle Wasserstein Regression GANs. - Matthew B. A. McDermott; Tom Yan; Tristan Naumann; Nathan Hunt; Harini Suresh; Peter Szolovits; Marzyeh Ghassemi (AAAI, 2018)

MIT-MEDG at SemEval-2018 Task 7: Semantic Relation Classification via Convolution Neural Network. - Di Jin; Franck Dernoncourt; Elena Sergeeva; Matthew B. A. McDermott; Geeticka Chauhan (SemEval@NAACL-HLT, 2018)

Machine Learning for Health (ML4H) Workshop at NeurIPS 2018. - Natalia Antropova; Andrew L. Beam; Brett K. Beaulieu-Jones; Irene Chen; Corey Chivers; Adrian V. Dalca; Samuel G. Finlayson; Madalina Fiterau; Jason Alan Fries; Marzyeh Ghassemi; Mike Hughes; Bruno Jedynak; et al. (CoRR, 2018)

Unsupervised Multimodal Representation Learning across Medical Images and Reports. - Tzu-Ming Harry Hsu; Wei-Hung Weng; Willie Boag; Matthew B. A. McDermott; Peter Szolovits (CoRR, 2018)

Rethinking clinical prediction: Why machine learning must consider year of care and feature aggregation. - Bret Nestor; Matthew B. A. McDermott; Geeticka Chauhan; Tristan Naumann; Michael C. Hughes; Anna Goldenberg; Marzyeh Ghassemi (CoRR, 2018)

A Framework for Relation Extraction Across Multiple Datasets in Multiple Domains. - Geeticka Chauhan; Matthew B. A. McDermott; Peter Szolovits (WNLP@ACL, 2019)

REflex: Flexible Framework for Relation Extraction in Multiple Domains. - Geeticka Chauhan; Matthew B. A. McDermott; Peter Szolovits (BioNLP@ACL, 2019)

Reproducibility in Machine Learning for Health. - Matthew B. A. McDermott; Shirly Wang; Nikki Marinsek; Rajesh Ranganath; Marzyeh Ghassemi; Luca Foschini 002 (RML@ICLR, 2019)

Clinically Accurate Chest X-Ray Report Generation. - Guanxiong Liu; Tzu-Ming Harry Hsu; Matthew B. A. McDermott; Willie Boag; Wei-Hung Weng; Peter Szolovits; Marzyeh Ghassemi (MLHC, 2019)

Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks. - Bret Nestor; Matthew B. A. McDermott; Willie Boag; Gabriela Berner; Tristan Naumann; Michael C. Hughes; Anna Goldenberg; Marzyeh Ghassemi (MLHC, 2019)

Cross-Language Aphasia Detection using Optimal Transport Domain Adaptation. - Aparna Balagopalan; Jekaterina Novikova; Matthew B. A. McDermott; Bret Nestor; Tristan Naumann; Marzyeh Ghassemi (ML4H@NeurIPS, 2019)

Baselines for Chest X-Ray Report Generation. - William Boag; Tzu-Ming Harry Hsu; Matthew B. A. McDermott; Gabriela Berner; Emily Alsentzer; Peter Szolovits (ML4H@NeurIPS, 2019)

Machine Learning for Health ( ML4H ) 2019 : What Makes Machine Learning in Medicine Different? - Adrian V. Dalca; Matthew B. A. McDermott; Emily Alsentzer; Samuel G. Finlayson; Michael Oberst; Fabian Falck; Corey Chivers; Andrew Beam; Tristan Naumann; Brett K. Beaulieu-Jones (ML4H@NeurIPS, 2019)

Publicly Available Clinical BERT Embeddings. - Emily Alsentzer; John R. Murphy; Willie Boag; Wei-Hung Weng; Di Jin; Tristan Naumann; Matthew B. A. McDermott (CoRR, 2019)

Approaching Small Molecule Prioritization as a Cross-Modal Information Retrieval Task through Coordinated Representation Learning. - Samuel G. Finlayson; Matthew B. A. McDermott; Alex V. Pickering; Scott L. Lipnick; William Yuan; Isaac S. Kohane (CoRR, 2019)

MIMIC-Extract: a data extraction, preprocessing, and representation pipeline for MIMIC-III. - Shirly Wang; Matthew B. A. McDermott; Geeticka Chauhan; Marzyeh Ghassemi; Michael C. Hughes; Tristan Naumann (CHIL, 2020)

Hurtful words: quantifying biases in clinical contextual word embeddings. - Haoran Zhang 003; Amy X. Lu; Mohamed Abdalla 001; Matthew B. A. McDermott; Marzyeh Ghassemi (CHIL, 2020)

CheXpert++: Approximating the CheXpert Labeler for Speed, Differentiability, and Probabilistic Output. - Matthew B. A. McDermott; Tzu-Ming Harry Hsu; Wei-Hung Weng; Marzyeh Ghassemi; Peter Szolovits (MLHC, 2020)

Machine Learning for Health (ML4H) 2020: Advancing Healthcare for All. - Suproteem K. Sarkar; Subhrajit Roy; Emily Alsentzer; Matthew B. A. McDermott; Fabian Falck; Ioana Bica; Griffin Adams; Stephen Pfohl; Stephanie L. Hyland (ML4H@NeurIPS, 2020)

ML4H Abstract Track 2019. - Matthew B. A. McDermott; Emily Alsentzer; Samuel G. Finlayson; Michael Oberst; Fabian Falck; Tristan Naumann; Brett K. Beaulieu-Jones; Adrian V. Dalca (CoRR, 2020)

CheXclusion: Fairness gaps in deep chest X-ray classifiers. - Laleh Seyyed-Kalantari; Guanxiong Liu; Matthew B. A. McDermott; Marzyeh Ghassemi (CoRR, 2020)

A Comprehensive Evaluation of Multi-task Learning and Multi-task Pre-training on EHR Time-series Data. - Matthew B. A. McDermott; Bret Nestor; Evan Kim; Wancong Zhang; Anna Goldenberg; Peter Szolovits; Marzyeh Ghassemi (CoRR, 2020)

ML4H Abstract Track 2020. - Emily Alsentzer; Matthew B. A. McDermott; Fabian Falck; Suproteem K. Sarkar; Subhrajit Roy; Stephanie L. Hyland (CoRR, 2020)

Deep Learning Benchmarks on L1000 Gene Expression Data. - Matthew B. A. McDermott; Jennifer Wang; Wen-Ning Zhao; Steven Sheridan; Peter Szolovits; Isaac S. Kohane; Stephen J. Haggarty; Roy H. Perlis (IEEE ACM Trans. Comput. Biol. Bioinform., 2020)

A comprehensive EHR timeseries pre-training benchmark. - Matthew B. A. McDermott; Bret Nestor; Evan Kim; Wancong Zhang; Anna Goldenberg; Peter Szolovits; Marzyeh Ghassemi (CHIL, 2021)

Machine Learning for Health (ML4H) 2021. - Subhrajit Roy; Stephen Pfohl; Girmaw Abebe Tadesse; Luis Oala; Fabian Falck; Yuyin Zhou; Liyue Shen; Ghada Zamzmi; Purity Mugambi; Ayah Zirikly; Matthew B. A. McDermott; Emily Alsentzer (ML4H@NeurIPS, 2021)

Cross-modal representation alignment of molecular structure and perturbation-induced transcriptional profiles. - Samuel G. Finlayson; Matthew B. A. McDermott; Alex V. Pickering; Scott L. Lipnick; Isaac S. Kohane (PSB, 2021)

CheXclusion: Fairness gaps in deep chest X-ray classifiers. - Laleh Seyyed-Kalantari; Guanxiong Liu; Matthew B. A. McDermott; Irene Y. Chen; Marzyeh Ghassemi (PSB, 2021)

Adversarial Contrastive Pre-training for Protein Sequences. - Matthew B. A. McDermott; Brendan Yap; Tzu-Ming Harry Hsu; Di Jin; Peter Szolovits (CoRR, 2021)

Rethinking Relational Encoding in Language Model: Pre-Training for General Sequences. - Matthew B. A. McDermott; Brendan Yap; Peter Szolovits; Marinka Zitnik (CoRR, 2021)

A collection of the accepted abstracts for the Machine Learning for Health (ML4H) symposium 2021. - Fabian Falck; Yuyin Zhou; Emma Rocheteau; Liyue Shen; Luis Oala; Girmaw Abebe; Subhrajit Roy; Stephen Pfohl; Emily Alsentzer; Matthew B. A. McDermott (CoRR, 2021)

Leveraging Structure and Knowledge in Clinical and Biomedical Representation Learning - Matthew B. A. McDermott (2022)

Event Stream GPT: A Data Pre-processing and Modeling Library for Generative, Pre-trained Transformers over Continuous-time Sequences of Complex Events. - Matthew B. A. McDermott; Bret Nestor; Peniel N. Argaw; Isaac S. Kohane (NeurIPS, 2023)

Event-Based Contrastive Learning for Medical Time Series. - Hyewon Jeong; Nassim Oufattole; Aparna Balagopalan; Matthew B. A. McDermott; Payal Chandak; Marzyeh Ghassemi; Collin M. Stultz (CoRR, 2023)

Structure-inducing pre-training. - Matthew B. A. McDermott; Brendan Yap; Peter Szolovits; Marinka Zitnik (Nat. Mac. Intell., 2023)

Conference on Health, Inference, and Learning (CHIL) 2024. - Tom J. Pollard; Edward Choi; Pankhuri Singhal; Michael C. Hughes; Elena Sizikova; Bobak Mortazavi; Irene Y. Chen; Fei Wang; Tasmie Sarker; Matthew B. A. McDermott; Marzyeh Ghassemi (CHIL, 2024)

Event-Based Contrastive Learning for Medical Time Series. - Nassim Oufattole; Hyewon Jeong; Matthew B. A. McDermott; Aparna Balagopalan; Bryan Jangeesingh; Marzyeh Ghassemi; Collin M. Stultz (MLHC, 2024)

A Closer Look at AUROC and AUPRC under Class Imbalance. - Matthew B. A. McDermott; Haoran Zhang 003; Lasse Hyldig Hansen; Giovanni Angelotti; Jack Gallifant (NeurIPS, 2024)

Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium. - Hyewon Jeong; Sarah Jabbour; Yuzhe Yang 003; Rahul Thapa; Hussein Mozannar; William Jongwon Han; Nikita Mehandru; Michael Wornow; Vladislav Lialin; Xin Liu 034; Alejandro Lozano; Jiacheng Zhu; et al. (CoRR, 2024)

meds_reader: A fast and efficient EHR processing library. - Ethan Steinberg; Michael Wornow; Suhana Bedi; Jason Alan Fries; Matthew B. A. McDermott; Nigam H. Shah (CoRR, 2024)

MEDS-Tab: Automated tabularization and baseline methods for MEDS datasets. - Nassim Oufattole; Teya S. Bergamaschi; Aleksia Kolo; Hyewon Jeong; Hanna Gaggin; Collin M. Stultz; Matthew B. A. McDermott (CoRR, 2024)

ACES: Automatic Cohort Extraction System for Event-Stream Datasets. - Justin Xu; Jack Gallifant; Alistair E. W. Johnson; Matthew B. A. McDermott (ICLR, 2025)

Foundation Model of Electronic Medical Records for Adaptive Risk Estimation. - Pawel Renc; Michal K. Grzeszczyk; Nassim Oufattole; Deirdre Goode; Yugang Jia; Szymon Bieganski; Matthew B. A. McDermott; Jaroslaw Was; Anthony E. Samir; Jonathan W. Cunningham; David W. Bates; Arkadiusz Sitek (CoRR, 2025)

BioClinical ModernBERT: A State-of-the-Art Long-Context Encoder for Biomedical and Clinical NLP. - Thomas Sounack; Joshua Davis; Brigitte N. Durieux; Antoine Chaffin; Tom J. Pollard; Eric Lehman; Alistair E. W. Johnson; Matthew B. A. McDermott; Tristan Naumann; Charlotta Lindvall (CoRR, 2025)