99 citations · 224 across the 16 of their papers we have counts for
16 papers
HealthAdminBench: Evaluating Computer-Use Agents on Healthcare Administration Tasks
Suhana Bedi, Ryan Welch, Ethan Steinberg +12
Healthcare administration accounts for over $1 trillion in annual spending, making it a promising target for LLM-based computer-use agents (CUAs). While clinical applications of LL…
Context Clues: Evaluating Long Context Models for Clinical Prediction Tasks on EHRs
Michael Wornow, Suhana Bedi, Miguel Angel Fuentes Hernandez +5
Foundation Models (FMs) trained on Electronic Health Records (EHRs) have achieved state-of-the-art results on numerous clinical prediction tasks. However, most existing EHR FMs hav…
Time-to-Event Pretraining for 3D Medical Imaging
Zepeng Huo, Jason Alan Fries, Alejandro Lozano +6
With the rise of medical foundation models and the growing availability of imaging data, scalable pretraining techniques offer a promising way to identify imaging biomarkers predic…
meds_reader: A fast and efficient EHR processing library
Ethan Steinberg, Michael Wornow, Suhana Bedi +3
The growing demand for machine learning in healthcare requires processing increasingly large electronic health record (EHR) datasets, but existing pipelines are not computationally…
INSPECT: A Multimodal Dataset for Pulmonary Embolism Diagnosis and Prognosis
Shih-Cheng Huang, Zepeng Huo, Ethan Steinberg +6
Synthesizing information from multiple data sources plays a crucial role in the practice of modern medicine. Current applications of artificial intelligence in medicine often focus…
A Multi-Center Study on the Adaptability of a Shared Foundation Model for Electronic Health Records
Lin Lawrence Guo, Jason Fries, Ethan Steinberg +6
Foundation models hold promise for transforming AI in healthcare by providing modular components that are easily adaptable to downstream healthcare tasks, making AI development mor…