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)

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)

Preparing a Clinical Support Model for Silent Mode in General Internal Medicine. - Bret Nestor; Liam G. McCoy; Amol Verma; Chloé Pou-Prom; Joshua Murray; Sebnem Kuzulugil; David Dai; Muhammad Mamdani; Anna Goldenberg; Marzyeh Ghassemi (MLHC, 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)

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)

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)

Satisfying Model Validity for Robust Clinical Machine Learning for Time-Series - Bret Nestor (2023)