6 papers
Deployment-Centered Evaluation: Predicting Query-Level Rejection Risk in a Clinical LLM System
Alyssa Unell, Miguel Fuentes, Brenna Li +4
Large language models (LLMs) are increasingly integrated into clinical systems, making it essential to evaluate the real-world utility of these systems. However, static benchmarks…
Adoption and Use of LLMs at an Academic Medical Center
Nigam H. Shah, Nerissa Ambers, Abby Pandya +55
While large language models (LLMs) can support clinical documentation needs, standalone tools struggle with "workflow friction" from manual data entry. We developed ChatEHR, a syst…
Training-Free Adaptation of New-Generation LLMs using Legacy Clinical Models
Sasha Ronaghi, Chloe Stanwyck, Asad Aali +4
Adapting language models to the clinical domain through continued pretraining and instruction tuning requires costly retraining for each new model generation. We propose Cross-Arch…
Structured Prompts Improve Evaluation of Language Models
Asad Aali, Muhammad Ahmed Mohsin, Vasiliki Bikia +15
As language models (LMs) are increasingly adopted across domains, high-quality benchmarking frameworks are essential for guiding deployment decisions. In practice, however, framewo…
Monitoring Deployed AI Systems in Health Care
Timothy Keyes, Alison Callahan, Abby S. Pandya +18
Post-deployment monitoring of artificial intelligence (AI) systems in health care is essential to ensure their safety, quality, and sustained benefit-and to support governance deci…
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…