10 citations · 14 across the 7 of their papers we have counts for
8 papers
A Living Benchmark for Information Retrieval from Electronic Health Records
Jordan L. Cahoon, Chloe O. Stanwyck, Sulaiman Somani +23
Large language model (LLM)-based clinical assistants are increasingly being integrated into electronic health record (EHR) systems, transforming how clinicians retrieve and synthes…
PhysicianBench: Evaluating LLM Agents in Real-World EHR Environments
Ruoqi Liu, Imran Q. Mohiuddin, Austin J. Schoeffler +10
We introduce PhysicianBench, a benchmark for evaluating LLM agents on physician tasks grounded in real clinical setting within electronic health record (EHR) environments. Existing…
Clinician input steers AI toward accurate and harmful recommendations
Ivan Lopez, Selin S. Everett, Bryan J. Bunning +10
Large language models (LLMs) are entering clinical workflows, yet evaluations rarely assess how clinician reasoning shapes model behavior during clinical interactions. Using 61 cur…
Retrieval-Augmented Guardrails for AI-Drafted Patient-Portal Messages: Error Taxonomy Construction and Large-Scale Evaluation
Wenyuan Chen, Fateme Nateghi Haredasht, Kameron C. Black +4
Asynchronous patient-clinician messaging via EHR portals is a growing source of clinician workload, prompting interest in large language models (LLMs) to assist with draft response…
MedFactEval and MedAgentBrief: A Framework and Workflow for Generating and Evaluating Factual Clinical Summaries
François Grolleau, Emily Alsentzer, Timothy Keyes +17
Evaluating factual accuracy in Large Language Model (LLM)-generated clinical text is a critical barrier to adoption, as expert review is unscalable for the continuous quality assur…
MedHELM: Holistic Evaluation of Large Language Models for Medical Tasks
Suhana Bedi, Hejie Cui, Miguel Fuentes +78
While large language models (LLMs) achieve near-perfect scores on medical licensing exams, these evaluations inadequately reflect the complexity and diversity of real-world clinica…
A Multi-Phase Analysis of Blood Culture Stewardship: Machine Learning Prediction, Expert Recommendation Assessment, and LLM Automation
Fatemeh Amrollahi, Nicholas Marshall, Fateme Nateghi Haredasht +10
Blood cultures are often over ordered without clear justification, straining healthcare resources and contributing to inappropriate antibiotic use pressures worsened by the global…
MedAgentBench: A Realistic Virtual EHR Environment to Benchmark Medical LLM Agents
Yixing Jiang, Kameron C. Black, Gloria Geng +4
Recent large language models (LLMs) have demonstrated significant advancements, particularly in their ability to serve as agents thereby surpassing their traditional role as chatbo…