Matthew B. A. McDermott

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 46

Top Topics

Relation Extraction

Multiple Domains

Machine Learning

Top Venues

Publications

Matthew B. A. McDermott, Lasse Hyldig Hansen, Haoran Zhang, Giovanni Angelotti, Jack Gallifant
A Closer Look at AUROC and AUPRC under Class Imbalance. CoRR (2024)
Justin Xu, Jack Gallifant, Alistair E. W. Johnson, Matthew B. A. McDermott
ACES: Automatic Cohort Extraction System for Event-Stream Datasets. CoRR (2024)
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
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium. CoRR (2024)
Matthew B. A. McDermott, Brendan Yap, Peter Szolovits, Marinka Zitnik
Structure-inducing pre-training. Nat. Mac. Intell. 5 (6) (2023)
Matthew B. A. McDermott, Bret Nestor, Peniel N. Argaw, Isaac S. Kohane
Event Stream GPT: A Data Pre-processing and Modeling Library for Generative, Pre-trained Transformers over Continuous-time Sequences of Complex Events. NeurIPS (2023)
Matthew B. A. McDermott, Bret Nestor, Peniel Argaw, Isaac S. Kohane
Event Stream GPT: A Data Pre-processing and Modeling Library for Generative, Pre-trained Transformers over Continuous-time Sequences of Complex Events. CoRR (2023)
Hyewon Jeong, Nassim Oufattole, Aparna Balagopalan, Matthew B. A. McDermott, Payal Chandak, Marzyeh Ghassemi, Collin M. Stultz
Event-Based Contrastive Learning for Medical Time Series. CoRR (2023)
Matthew B. A. McDermott, Bret Nestor, Evan Kim, Wancong Zhang, Anna Goldenberg, Peter Szolovits, Marzyeh Ghassemi
A comprehensive EHR timeseries pre-training benchmark. CHIL (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
Machine Learning for Health (ML4H) 2021. ML4H@NeurIPS (2021)
Laleh Seyyed-Kalantari, Guanxiong Liu, Matthew B. A. McDermott, Irene Y. Chen, Marzyeh Ghassemi
CheXclusion: Fairness gaps in deep chest X-ray classifiers. PSB (2021)
Matthew B. A. McDermott, Brendan Yap, Peter Szolovits, Marinka Zitnik
Rethinking Relational Encoding in Language Model: Pre-Training for General Sequences. CoRR (2021)
Fabian Falck, Yuyin Zhou, Emma Rocheteau, Liyue Shen, Luis Oala, Girmaw Abebe, Subhrajit Roy, Stephen Pfohl, Emily Alsentzer, Matthew B. A. McDermott
A collection of the accepted abstracts for the Machine Learning for Health (ML4H) symposium 2021. CoRR (2021)
Samuel G. Finlayson, Matthew B. A. McDermott, Alex V. Pickering, Scott L. Lipnick, Isaac S. Kohane
Cross-modal representation alignment of molecular structure and perturbation-induced transcriptional profiles. PSB (2021)
Matthew B. A. McDermott, Brendan Yap, Tzu-Ming Harry Hsu, Di Jin, Peter Szolovits
Adversarial Contrastive Pre-training for Protein Sequences. CoRR (2021)
Haoran Zhang, Amy X. Lu, Mohamed Abdalla, Matthew B. A. McDermott, Marzyeh Ghassemi
Hurtful Words: Quantifying Biases in Clinical Contextual Word Embeddings. CoRR (2020)
Matthew B. A. McDermott, Tzu-Ming Harry Hsu, Wei-Hung Weng, Marzyeh Ghassemi, Peter Szolovits
CheXpert++: Approximating the CheXpert Labeler for Speed, Differentiability, and Probabilistic Output. MLHC (2020)
Shirly Wang, Matthew B. A. McDermott, Geeticka Chauhan, Marzyeh Ghassemi, Michael C. Hughes, Tristan Naumann
MIMIC-Extract: a data extraction, preprocessing, and representation pipeline for MIMIC-III. CHIL (2020)
Suproteem K. Sarkar, Subhrajit Roy, Emily Alsentzer, Matthew B. A. McDermott, Fabian Falck, Ioana Bica, Griffin Adams, Stephen Pfohl, Stephanie L. Hyland
Machine Learning for Health (ML4H) 2020: Advancing Healthcare for All. ML4H@NeurIPS (2020)
Haoran Zhang, Amy X. Lu, Mohamed Abdalla, Matthew B. A. McDermott, Marzyeh Ghassemi
Hurtful words: quantifying biases in clinical contextual word embeddings. CHIL (2020)
Matthew B. A. McDermott, Tzu-Ming Harry Hsu, Wei-Hung Weng, Marzyeh Ghassemi, Peter Szolovits
CheXpert++: Approximating the CheXpert labeler for Speed, Differentiability, and Probabilistic Output. CoRR (2020)
Matthew B. A. McDermott, Bret Nestor, Evan Kim, Wancong Zhang, Anna Goldenberg, Peter Szolovits, Marzyeh Ghassemi
A Comprehensive Evaluation of Multi-task Learning and Multi-task Pre-training on EHR Time-series Data. CoRR (2020)
Emily Alsentzer, Matthew B. A. McDermott, Fabian Falck, Suproteem K. Sarkar, Subhrajit Roy, Stephanie L. Hyland
ML4H Abstract Track 2020. CoRR (2020)
Matthew B. A. McDermott, Emily Alsentzer, Samuel G. Finlayson, Michael Oberst, Fabian Falck, Tristan Naumann, Brett K. Beaulieu-Jones, Adrian V. Dalca
ML4H Abstract Track 2019. CoRR (2020)
Matthew B. A. McDermott, Jennifer Wang, Wen-Ning Zhao, Steven Sheridan, Peter Szolovits, Isaac S. Kohane, Stephen J. Haggarty, Roy H. Perlis
Deep Learning Benchmarks on L1000 Gene Expression Data. IEEE ACM Trans. Comput. Biol. Bioinform. 17 (6) (2020)
Laleh Seyyed-Kalantari, Guanxiong Liu, Matthew B. A. McDermott, Marzyeh Ghassemi
CheXclusion: Fairness gaps in deep chest X-ray classifiers. CoRR (2020)
Matthew B. A. McDermott, Shirly Wang, Nikki Marinsek, Rajesh Ranganath, Marzyeh Ghassemi, Luca Foschini
Reproducibility in Machine Learning for Health. CoRR (2019)
Samuel G. Finlayson, Matthew B. A. McDermott, Alex V. Pickering, Scott L. Lipnick, William Yuan, Isaac S. Kohane
Approaching Small Molecule Prioritization as a Cross-Modal Information Retrieval Task through Coordinated Representation Learning. CoRR (2019)
Guanxiong Liu, Tzu-Ming Harry Hsu, Matthew B. A. McDermott, Willie Boag, Wei-Hung Weng, Peter Szolovits, Marzyeh Ghassemi
Clinically Accurate Chest X-Ray Report Generation. MLHC (2019)
Geeticka Chauhan, Matthew B. A. McDermott, Peter Szolovits
A Framework for Relation Extraction Across Multiple Datasets in Multiple Domains. WNLP@ACL (2019)
Geeticka Chauhan, Matthew B. A. McDermott, Peter Szolovits
REflex: Flexible Framework for Relation Extraction in Multiple Domains. CoRR (2019)
Emily Alsentzer, John R. Murphy, Willie Boag, Wei-Hung Weng, Di Jin, Tristan Naumann, Matthew B. A. McDermott
Publicly Available Clinical BERT Embeddings. CoRR (2019)
Shirly Wang, Matthew B. A. McDermott, Geeticka Chauhan, Michael C. Hughes, Tristan Naumann, Marzyeh Ghassemi
MIMIC-Extract: A Data Extraction, Preprocessing, and Representation Pipeline for MIMIC-III. CoRR (2019)
Aparna Balagopalan, Jekaterina Novikova, Matthew B. A. McDermott, Bret Nestor, Tristan Naumann, Marzyeh Ghassemi
Cross-Language Aphasia Detection using Optimal Transport Domain Adaptation. ML4H@NeurIPS (2019)
Geeticka Chauhan, Matthew B. A. McDermott, Peter Szolovits
REflex: Flexible Framework for Relation Extraction in Multiple Domains. BioNLP@ACL (2019)
Aparna Balagopalan, Jekaterina Novikova, Matthew B. A. McDermott, Bret Nestor, Tristan Naumann, Marzyeh Ghassemi
Cross-Language Aphasia Detection using Optimal Transport Domain Adaptation. CoRR (2019)
Guanxiong Liu, Tzu-Ming Harry Hsu, Matthew B. A. McDermott, Willie Boag, Wei-Hung Weng, Peter Szolovits, Marzyeh Ghassemi
Clinically Accurate Chest X-Ray Report Generation. CoRR (2019)
William Boag, Tzu-Ming Harry Hsu, Matthew B. A. McDermott, Gabriela Berner, Emily Alsentzer, Peter Szolovits
Baselines for Chest X-Ray Report Generation. ML4H@NeurIPS (2019)
Bret Nestor, Matthew B. A. McDermott, Willie Boag, Gabriela Berner, Tristan Naumann, Michael C. Hughes, Anna Goldenberg, Marzyeh Ghassemi
Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks. MLHC (2019)
Bret Nestor, Matthew B. A. McDermott, Willie Boag, Gabriela Berner, Tristan Naumann, Michael C. Hughes, Anna Goldenberg, Marzyeh Ghassemi
Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks. CoRR (2019)
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
Machine Learning for Health ( ML4H ) 2019 : What Makes Machine Learning in Medicine Different? ML4H@NeurIPS (2019)
Matthew B. A. McDermott, Shirly Wang, Nikki Marinsek, Rajesh Ranganath, Marzyeh Ghassemi, Luca Foschini
Reproducibility in Machine Learning for Health. RML@ICLR (2019)
Tzu-Ming Harry Hsu, Wei-Hung Weng, Willie Boag, Matthew B. A. McDermott, Peter Szolovits
Unsupervised Multimodal Representation Learning across Medical Images and Reports. CoRR (2018)
Matthew B. A. McDermott, Tom Yan, Tristan Naumann, Nathan Hunt, Harini Suresh, Peter Szolovits, Marzyeh Ghassemi
Semi-Supervised Biomedical Translation With Cycle Wasserstein Regression GANs. AAAI (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
Machine Learning for Health (ML4H) Workshop at NeurIPS 2018. CoRR (2018)
Bret Nestor, Matthew B. A. McDermott, Geeticka Chauhan, Tristan Naumann, Michael C. Hughes, Anna Goldenberg, Marzyeh Ghassemi
Rethinking clinical prediction: Why machine learning must consider year of care and feature aggregation. CoRR (2018)
Di Jin, Franck Dernoncourt, Elena Sergeeva, Matthew B. A. McDermott, Geeticka Chauhan
MIT-MEDG at SemEval-2018 Task 7: Semantic Relation Classification via Convolution Neural Network. SemEval@NAACL-HLT (2018)