Matthew B. A. McDermott

62 papers A* 4Misc 2Journal 34Unranked 18

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Efficient Variance-reduced Estimation from Generative EHR Models: The SCOPE and REACH Estimators. CoRR Luke Solo, Matthew B. A. McDermott, William F. Parker, Bashar Ramadan, Michael C. Burkhart, Brett K. Beaulieu-Jones
2026	J	`jnl`	EveryQuery: Zero-Shot Clinical Prediction via Task-Conditioned Pretraining over Electronic Health Records. CoRR Payal Chandak, Gregory Kondas, Isaac S. Kohane, Matthew B. A. McDermott
2025	A*	`conf`	ACES: Automatic Cohort Extraction System for Event-Stream Datasets. ICLR Justin Xu, Jack Gallifant, Alistair E. W. Johnson, Matthew B. A. McDermott
2025	J	`jnl`	BioClinical ModernBERT: A State-of-the-Art Long-Context Encoder for Biomedical and Clinical NLP. CoRR 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
2025	J	`jnl`	Foundation Model of Electronic Medical Records for Adaptive Risk Estimation. CoRR 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
2025	—	`conf`	MEDS: Building Models and Tools in a Reproducible Health AI Ecosystem. KDD (2) Matthew B. A. McDermott, Justin Xu, Teya S. Bergamaschi, Hyewon Jeong, Simon A. Lee, Nassim Oufattole, Patrick Rockenschaub, Kamile Stankeviciute, Ethan Steinberg, Jimeng Sun, Robin Van De Water, Michael Wornow, John Wu, Zhenbang Wu
2025	J	`jnl`	Reflections from Research Roundtables at the Conference on Health, Inference, and Learning (CHIL) 2025. CoRR Emily Alsentzer, Marie-Laure Charpignon, Bill Chen, Niharika D'Souza, Jason A. Fries, Yixing Jiang, Aparajita Kashyap, Chanwoo Kim, Simon A. Lee, Aishwarya Mandyam, Ashery Christopher Mbilinyi, Nikita Mehandru, Nitish Nagesh, Brighton Nuwagira, Emma Pierson, Arvind Pillai, Akane Sano, Tanveer F. Syeda-Mahmood, Shashank Yadav, Elias Adhanom, Muhammad Umar Afza, Amelia Archer, Suhana Bedi, Vasiliki Bikia, Trenton Chang, George H. Chen, Winston Chen, Erica Chiang, Edward Choi, Octavia Ciora, Paz Dozie-Nnamah, Shaza Elsharief, Matthew Engelhard, Ali Eshragh, Jean Feng, Josh Fessel, Scott L. Fleming, Kei Sen Fong, Thomas Frost, Soham Gadgil, Judy Gichoya, Leeor Hershkovich, Sujeong Im, Bhavya Jain, Vincent Jeanselme, Furong Jia, Qixuan Jin, Yuxuan Jin, Daniel Kapash, Geetika Kapoor, Behdokht Kiafar, Matthias Kleiner, Stefan Kraft, Annika Kumar, Daeun Kyung, Zhongyuan Liang, Joanna Lin, Qianchu Liu, Chang Liu, Hongzhou Luan, Chris Lunt, Leopoldo Julian Lechuga López, Matthew B. A. McDermott, Shahriar Noroozizadeh, Connor O'Brien, YongKyung Oh, Mixail Ota, Stephen Pfohl, Meagan Pi, Tanmoy Sarkar Pias, Emma Rocheteau, Avishaan Sethi, Toru Shirakawa, Anita Silver, Neha Simha, Kamile Stankeviciute, Max Sunog, Peter Szolovits, Shengpu Tang, Jialu Tang, Aaron Tierney, John Valdovinos, Byron Wallace, Will Ke Wang, Peter Washington, Jeremy C. Weiss, Daniel Wolfe, Emily Wong, Hye Sun Yun, Xiaoman Zhang, Xiao Yu Cindy Zhang, Hayoung Jeong, Kaveri A. Thakoor
2024	A*	`conf`	A Closer Look at AUROC and AUPRC under Class Imbalance. NeurIPS Matthew B. A. McDermott, Haoran Zhang, Lasse Hyldig Hansen, Giovanni Angelotti, Jack Gallifant
2024	J	`jnl`	A Closer Look at AUROC and AUPRC under Class Imbalance. CoRR Matthew B. A. McDermott, Lasse Hyldig Hansen, Haoran Zhang, Giovanni Angelotti, Jack Gallifant
2024	J	`jnl`	ACES: Automatic Cohort Extraction System for Event-Stream Datasets. CoRR Justin Xu, Jack Gallifant, Alistair E. W. Johnson, Matthew B. A. McDermott
2024	—	`conf`	Conference on Health, Inference, and Learning (CHIL) 2024. CHIL 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
2024	—	`conf`	Event-Based Contrastive Learning for Medical Time Series. MLHC Nassim Oufattole, Hyewon Jeong, Matthew B. A. McDermott, Aparna Balagopalan, Bryan Jangeesingh, Marzyeh Ghassemi, Collin M. Stultz
2024	J	`jnl`	MEDS-Tab: Automated tabularization and baseline methods for MEDS datasets. CoRR Nassim Oufattole, Teya S. Bergamaschi, Aleksia Kolo, Hyewon Jeong, Hanna Gaggin, Collin M. Stultz, Matthew B. A. McDermott
2024	J	`jnl`	Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium. CoRR Hyewon Jeong, Sarah Jabbour, Yuzhe Yang, Rahul Thapa, Hussein Mozannar, William Jongwon Han, Nikita Mehandru, Michael Wornow, Vladislav Lialin, Xin Liu, Alejandro Lozano, Jiacheng Zhu, Rafal Dariusz Kocielnik, Keith Harrigian, Haoran Zhang, Edward Lee, Milos Vukadinovic, Aparna Balagopalan, Vincent Jeanselme, Katherine Matton, Ilker Demirel, Jason A. Fries, Parisa Rashidi, Brett K. Beaulieu-Jones, Xuhai Orson Xu, Matthew B. A. McDermott, Tristan Naumann, Monica Agrawal, Marinka Zitnik, Berk Ustun, Edward Choi, Kristen Yeom, Gamze Gürsoy, Marzyeh Ghassemi, Emma Pierson, George H. Chen, Sanjat Kanjilal, Michael Oberst, Linying Zhang, Harvineet Singh, Tom Hartvigsen, Helen Zhou, Chinasa T. Okolo
2024	J	`jnl`	meds_reader: A fast and efficient EHR processing library. CoRR Ethan Steinberg, Michael Wornow, Suhana Bedi, Jason Alan Fries, Matthew B. A. McDermott, Nigam H. Shah
2023	A*	`conf`	Event Stream GPT: A Data Pre-processing and Modeling Library for Generative, Pre-trained Transformers over Continuous-time Sequences of Complex Events. NeurIPS Matthew B. A. McDermott, Bret Nestor, Peniel N. Argaw, Isaac S. Kohane
2023	J	`jnl`	Event Stream GPT: A Data Pre-processing and Modeling Library for Generative, Pre-trained Transformers over Continuous-time Sequences of Complex Events. CoRR Matthew B. A. McDermott, Bret Nestor, Peniel N. Argaw, Isaac S. Kohane
2023	J	`jnl`	Event-Based Contrastive Learning for Medical Time Series. CoRR Hyewon Jeong, Nassim Oufattole, Aparna Balagopalan, Matthew B. A. McDermott, Payal Chandak, Marzyeh Ghassemi, Collin M. Stultz
2023	J	`jnl`	Structure-inducing pre-training. Nat. Mac. Intell. Matthew B. A. McDermott, Brendan Yap, Peter Szolovits, Marinka Zitnik
2022	—	`—`	Leveraging Structure and Knowledge in Clinical and Biomedical Representation Learning Matthew B. A. McDermott
2021	J	`jnl`	A collection of the accepted abstracts for the Machine Learning for Health (ML4H) symposium 2021. CoRR Fabian Falck, Yuyin Zhou, Emma Rocheteau, Liyue Shen, Luis Oala, Girmaw Abebe, Subhrajit Roy, Stephen Pfohl, Emily Alsentzer, Matthew B. A. McDermott
2021	—	`conf`	A comprehensive EHR timeseries pre-training benchmark. CHIL Matthew B. A. McDermott, Bret Nestor, Evan Kim, Wancong Zhang, Anna Goldenberg, Peter Szolovits, Marzyeh Ghassemi
2021	J	`jnl`	Adversarial Contrastive Pre-training for Protein Sequences. CoRR Matthew B. A. McDermott, Brendan Yap, Tzu-Ming Harry Hsu, Di Jin, Peter Szolovits
2021	Misc	`conf`	CheXclusion: Fairness gaps in deep chest X-ray classifiers. PSB Laleh Seyyed-Kalantari, Guanxiong Liu, Matthew B. A. McDermott, Irene Y. Chen, Marzyeh Ghassemi
2021	Misc	`conf`	Cross-modal representation alignment of molecular structure and perturbation-induced transcriptional profiles. PSB Samuel G. Finlayson, Matthew B. A. McDermott, Alex V. Pickering, Scott L. Lipnick, Isaac S. Kohane
2021	—	`conf`	Machine Learning for Health (ML4H) 2021. ML4H@NeurIPS 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
2021	—	`ed.`	Machine Learning for Health, ML4H@NeurIPS 2021, 04 December 2021, Virtual Event. ML4H@NeurIPS Subhrajit Roy, Stephen Pfohl, Emma Rocheteau, Girmaw Abebe Tadesse, Luis Oala, Fabian Falck, Yuyin Zhou, Liyue Shen, Ghada Zamzmi, Purity Mugambi, Ayah Zirikly, Matthew B. A. McDermott, Emily Alsentzer
2021	J	`jnl`	Rethinking Relational Encoding in Language Model: Pre-Training for General Sequences. CoRR Matthew B. A. McDermott, Brendan Yap, Peter Szolovits, Marinka Zitnik
2020	J	`jnl`	A Comprehensive Evaluation of Multi-task Learning and Multi-task Pre-training on EHR Time-series Data. CoRR Matthew B. A. McDermott, Bret Nestor, Evan Kim, Wancong Zhang, Anna Goldenberg, Peter Szolovits, Marzyeh Ghassemi
2020	J	`jnl`	CheXclusion: Fairness gaps in deep chest X-ray classifiers. CoRR Laleh Seyyed-Kalantari, Guanxiong Liu, Matthew B. A. McDermott, Marzyeh Ghassemi
2020	—	`conf`	CheXpert++: Approximating the CheXpert Labeler for Speed, Differentiability, and Probabilistic Output. MLHC Matthew B. A. McDermott, Tzu-Ming Harry Hsu, Wei-Hung Weng, Marzyeh Ghassemi, Peter Szolovits
2020	J	`jnl`	CheXpert++: Approximating the CheXpert labeler for Speed, Differentiability, and Probabilistic Output. CoRR Matthew B. A. McDermott, Tzu-Ming Harry Hsu, Wei-Hung Weng, Marzyeh Ghassemi, Peter Szolovits
2020	J	`jnl`	Deep Learning Benchmarks on L1000 Gene Expression Data. IEEE ACM Trans. Comput. Biol. Bioinform. Matthew B. A. McDermott, Jennifer Wang, Wen-Ning Zhao, Steven Sheridan, Peter Szolovits, Isaac S. Kohane, Stephen J. Haggarty, Roy H. Perlis
2020	J	`jnl`	Hurtful Words: Quantifying Biases in Clinical Contextual Word Embeddings. CoRR Haoran Zhang, Amy X. Lu, Mohamed Abdalla, Matthew B. A. McDermott, Marzyeh Ghassemi
2020	—	`conf`	Hurtful words: quantifying biases in clinical contextual word embeddings. CHIL Haoran Zhang, Amy X. Lu, Mohamed Abdalla, Matthew B. A. McDermott, Marzyeh Ghassemi
2020	—	`conf`	MIMIC-Extract: a data extraction, preprocessing, and representation pipeline for MIMIC-III. CHIL Shirly Wang, Matthew B. A. McDermott, Geeticka Chauhan, Marzyeh Ghassemi, Michael C. Hughes, Tristan Naumann
2020	J	`jnl`	ML4H Abstract Track 2019. CoRR Matthew B. A. McDermott, Emily Alsentzer, Samuel G. Finlayson, Michael Oberst, Fabian Falck, Tristan Naumann, Brett K. Beaulieu-Jones, Adrian V. Dalca
2020	J	`jnl`	ML4H Abstract Track 2020. CoRR Emily Alsentzer, Matthew B. A. McDermott, Fabian Falck, Suproteem K. Sarkar, Subhrajit Roy, Stephanie L. Hyland
2020	—	`conf`	Machine Learning for Health (ML4H) 2020: Advancing Healthcare for All. ML4H@NeurIPS Suproteem K. Sarkar, Subhrajit Roy, Emily Alsentzer, Matthew B. A. McDermott, Fabian Falck, Ioana Bica, Griffin Adams, Stephen Pfohl, Stephanie L. Hyland
2020	—	`ed.`	Machine Learning for Health Workshop, ML4H@NeurIPS 2020, Virtual Event, 11 December 2020 ML4H@NeurIPS Emily Alsentzer, Matthew B. A. McDermott, Fabian Falck, Suproteem K. Sarkar, Subhrajit Roy, Stephanie L. Hyland
2019	—	`conf`	A Framework for Relation Extraction Across Multiple Datasets in Multiple Domains. WNLP@ACL Geeticka Chauhan, Matthew B. A. McDermott, Peter Szolovits
2019	J	`jnl`	Approaching Small Molecule Prioritization as a Cross-Modal Information Retrieval Task through Coordinated Representation Learning. CoRR Samuel G. Finlayson, Matthew B. A. McDermott, Alex V. Pickering, Scott L. Lipnick, William Yuan, Isaac S. Kohane
2019	—	`conf`	Baselines for Chest X-Ray Report Generation. ML4H@NeurIPS William Boag, Tzu-Ming Harry Hsu, Matthew B. A. McDermott, Gabriela Berner, Emily Alsentzer, Peter Szolovits
2019	—	`conf`	Clinically Accurate Chest X-Ray Report Generation. MLHC Guanxiong Liu, Tzu-Ming Harry Hsu, Matthew B. A. McDermott, Willie Boag, Wei-Hung Weng, Peter Szolovits, Marzyeh Ghassemi
2019	J	`jnl`	Clinically Accurate Chest X-Ray Report Generation. CoRR Guanxiong Liu, Tzu-Ming Harry Hsu, Matthew B. A. McDermott, Willie Boag, Wei-Hung Weng, Peter Szolovits, Marzyeh Ghassemi
2019	—	`conf`	Cross-Language Aphasia Detection using Optimal Transport Domain Adaptation. ML4H@NeurIPS Aparna Balagopalan, Jekaterina Novikova, Matthew B. A. McDermott, Bret Nestor, Tristan Naumann, Marzyeh Ghassemi
2019	J	`jnl`	Cross-Language Aphasia Detection using Optimal Transport Domain Adaptation. CoRR Aparna Balagopalan, Jekaterina Novikova, Matthew B. A. McDermott, Bret Nestor, Tristan Naumann, Marzyeh Ghassemi
2019	—	`conf`	Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks. MLHC Bret Nestor, Matthew B. A. McDermott, Willie Boag, Gabriela Berner, Tristan Naumann, Michael C. Hughes, Anna Goldenberg, Marzyeh Ghassemi
2019	J	`jnl`	Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks. CoRR Bret Nestor, Matthew B. A. McDermott, Willie Boag, Gabriela Berner, Tristan Naumann, Michael C. Hughes, Anna Goldenberg, Marzyeh Ghassemi
2019	J	`jnl`	MIMIC-Extract: A Data Extraction, Preprocessing, and Representation Pipeline for MIMIC-III. CoRR Shirly Wang, Matthew B. A. McDermott, Geeticka Chauhan, Michael C. Hughes, Tristan Naumann, Marzyeh Ghassemi
2019	—	`conf`	Machine Learning for Health ( ML4H ) 2019 : What Makes Machine Learning in Medicine Different? ML4H@NeurIPS 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
2019	—	`ed.`	Machine Learning for Health Workshop, ML4H@NeurIPS 2019, Vancouver, BC, Canada, 13 December 2019 ML4H@NeurIPS Adrian V. Dalca, Matthew B. A. McDermott, Emily Alsentzer, Samuel G. Finlayson, Michael Oberst, Fabian Falck, Brett K. Beaulieu-Jones
2019	J	`jnl`	Publicly Available Clinical BERT Embeddings. CoRR Emily Alsentzer, John R. Murphy, Willie Boag, Wei-Hung Weng, Di Jin, Tristan Naumann, Matthew B. A. McDermott
2019	—	`conf`	REflex: Flexible Framework for Relation Extraction in Multiple Domains. BioNLP@ACL Geeticka Chauhan, Matthew B. A. McDermott, Peter Szolovits
2019	J	`jnl`	REflex: Flexible Framework for Relation Extraction in Multiple Domains. CoRR Geeticka Chauhan, Matthew B. A. McDermott, Peter Szolovits
2019	—	`conf`	Reproducibility in Machine Learning for Health. RML@ICLR Matthew B. A. McDermott, Shirly Wang, Nikki Marinsek, Rajesh Ranganath, Marzyeh Ghassemi, Luca Foschini
2019	J	`jnl`	Reproducibility in Machine Learning for Health. CoRR Matthew B. A. McDermott, Shirly Wang, Nikki Marinsek, Rajesh Ranganath, Marzyeh Ghassemi, Luca Foschini
2018	—	`conf`	MIT-MEDG at SemEval-2018 Task 7: Semantic Relation Classification via Convolution Neural Network. SemEval@NAACL-HLT Di Jin, Franck Dernoncourt, Elena Sergeeva, Matthew B. A. McDermott, Geeticka Chauhan
2018	J	`jnl`	Machine Learning for Health (ML4H) Workshop at NeurIPS 2018. CoRR 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, Jasvinder S. Kandola, Matthew B. A. McDermott, Tristan Naumann, Peter Schulam, Farah Shamout, Alexandre Yahi
2018	J	`jnl`	Rethinking clinical prediction: Why machine learning must consider year of care and feature aggregation. CoRR Bret Nestor, Matthew B. A. McDermott, Geeticka Chauhan, Tristan Naumann, Michael C. Hughes, Anna Goldenberg, Marzyeh Ghassemi
2018	A*	`conf`	Semi-Supervised Biomedical Translation With Cycle Wasserstein Regression GANs. AAAI Matthew B. A. McDermott, Tom Yan, Tristan Naumann, Nathan Hunt, Harini Suresh, Peter Szolovits, Marzyeh Ghassemi
2018	J	`jnl`	Unsupervised Multimodal Representation Learning across Medical Images and Reports. CoRR Tzu-Ming Harry Hsu, Wei-Hung Weng, Willie Boag, Matthew B. A. McDermott, Peter Szolovits