99 citations · 133 across the 5 of their papers we have counts for
5 papers
MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records
Scott L. Fleming, Alejandro Lozano, William J. Haberkorn +27
The ability of large language models (LLMs) to follow natural language instructions with human-level fluency suggests many opportunities in healthcare to reduce administrative burd…
The Shaky Foundations of Clinical Foundation Models: A Survey of Large Language Models and Foundation Models for EMRs
Michael Wornow, Yizhe Xu, Rahul Thapa +6
The successes of foundation models such as ChatGPT and AlphaFold have spurred significant interest in building similar models for electronic medical records (EMRs) to improve patie…
Treatment Heterogeneity for Survival Outcomes
Yizhe Xu, Nikolaos Ignatiadis, Erik Sverdrup +3
Estimation of conditional average treatment effects (CATEs) plays an essential role in modern medicine by informing treatment decision-making at a patient level. Several metalearne…
Ontology-driven weak supervision for clinical entity classification in electronic health records
Jason A. Fries, Ethan Steinberg, Saelig Khattar +4
In the electronic health record, using clinical notes to identify entities such as disorders and their temporality (e.g. the order of an event relative to a time index) can inform…
Missingness as Stability: Understanding the Structure of Missingness in Longitudinal EHR data and its Impact on Reinforcement Learning in Healthcare
Scott L. Fleming, Kuhan Jeyapragasan, Tony Duan +4
There is an emerging trend in the reinforcement learning for healthcare literature. In order to prepare longitudinal, irregularly sampled, clinical datasets for reinforcement learn…