Matthew B. A. McDermott

According to our database, Matthew B. A. McDermott authored at least 36 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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, 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 Gursoy, Marzyeh Ghassemi, Emma Pierson, George H. Chen, Sanjat Kanjilal, Michael Oberst, Linying Zhang, Harvineet Singh, Tom Hartvigsen, Helen Zhou, Chinasa T. Okolo

CoRR, 2024

A Closer Look at AUROC and AUPRC under Class Imbalance.

Matthew B. A. McDermott, Lasse Hyldig Hansen, Haoran Zhang, Giovanni Angelotti, Jack Gallifant

CoRR, 2024

2023

Structure-inducing pre-training.

Matthew B. A. McDermott, Brendan Yap, Peter Szolovits, Marinka Zitnik

Nat. Mac. Intell., June, 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

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

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

Rethinking Relational Encoding in Language Model: Pre-Training for General Sequences.

Matthew B. A. McDermott, Brendan Yap, Peter Szolovits, Marinka Zitnik

CoRR, 2021

Adversarial Contrastive Pre-training for Protein Sequences.

Matthew B. A. McDermott, Brendan Yap, Tzu-Ming Harry Hsu, Di Jin, Peter Szolovits

CoRR, 2021

CheXclusion: Fairness gaps in deep chest X-ray classifiers.

Laleh Seyyed-Kalantari, Guanxiong Liu, Matthew B. A. McDermott, Irene Y. Chen, Marzyeh Ghassemi

Proceedings of the Biocomputing 2021: Proceedings of the Pacific Symposium, 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

Proceedings of the Biocomputing 2021: Proceedings of the Pacific Symposium, 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

Proceedings of the Machine Learning for Health, 2021

A comprehensive EHR timeseries pre-training benchmark.

Matthew B. A. McDermott, Bret Nestor, Evan Kim, Wancong Zhang, Anna Goldenberg, Peter Szolovits, Marzyeh Ghassemi

Proceedings of the ACM CHIL '21: ACM Conference on Health, 2021

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

ML4H Abstract Track 2020.

Emily Alsentzer, Matthew B. A. McDermott, Fabian Falck, Suproteem K. Sarkar, Subhrajit Roy, Stephanie L. Hyland

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

CheXclusion: Fairness gaps in deep chest X-ray classifiers.

Laleh Seyyed-Kalantari, Guanxiong Liu, Matthew B. A. McDermott, Marzyeh Ghassemi

CoRR, 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

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

Proceedings of the Machine Learning for Health Workshop, 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

Proceedings of the Machine Learning for Healthcare Conference, 2020

Hurtful words: quantifying biases in clinical contextual word embeddings.

Haoran Zhang, Amy X. Lu, Mohamed Abdalla, Matthew B. A. McDermott, Marzyeh Ghassemi

Proceedings of the ACM CHIL '20: ACM Conference on Health, 2020

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

Proceedings of the ACM CHIL '20: ACM Conference on Health, 2020

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

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

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

Proceedings of the Machine Learning for Health Workshop, 2019

Baselines for Chest X-Ray Report Generation.

William Boag, Tzu-Ming Harry Hsu, Matthew B. A. McDermott, Gabriela Berner, Emily Alsentzer, Peter Szolovits

Proceedings of the Machine Learning for Health Workshop, 2019

Cross-Language Aphasia Detection using Optimal Transport Domain Adaptation.

Aparna Balagopalan, Jekaterina Novikova, Matthew B. A. McDermott, Bret Nestor, Tristan Naumann, Marzyeh Ghassemi

Proceedings of the Machine Learning for Health Workshop, 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

Proceedings of the Machine Learning for Healthcare Conference, 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

Proceedings of the Machine Learning for Healthcare Conference, 2019

Reproducibility in Machine Learning for Health.

Matthew B. A. McDermott, Shirly Wang, Nikki Marinsek, Rajesh Ranganath, Marzyeh Ghassemi, Luca Foschini

Proceedings of the Reproducibility in Machine Learning, 2019

REflex: Flexible Framework for Relation Extraction in Multiple Domains.

Geeticka Chauhan, Matthew B. A. McDermott, Peter Szolovits

Proceedings of the 18th BioNLP Workshop and Shared Task, 2019

A Framework for Relation Extraction Across Multiple Datasets in Multiple Domains.

Geeticka Chauhan, Matthew B. A. McDermott, Peter Szolovits

Proceedings of the 2019 Workshop on Widening NLP@ACL 2019, Florence, Italy, July 28, 2019, 2019

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

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

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, Jasvinder S. Kandola, Matthew B. A. McDermott, Tristan Naumann, Peter Schulam, Farah Shamout, Alexandre Yahi

CoRR, 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

Proceedings of The 12th International Workshop on Semantic Evaluation, 2018

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

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018