From the 1 of 7 linked papers with an AI index.
6 citations · 6 across the 2 of their papers we have counts for
5 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…
CARE: A Conformal Safety Layer for Medical Summarization
Suhana Bedi, Bridget Lin, Anson Y. Zhou +5
Large language models (LLMs) are increasingly used for medical summarization, but their outputs can omit medically important information and introduce unsupported claims. Existing…
Quantifying and Mitigating Premature Closure in Frontier LLMs
Rebecca Handler, Suhana Bedi, Nigam Shah
Premature closure, or committing to a conclusion before sufficient information is available, is a recognized contributor to diagnostic error but remains underexamined in large lang…
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…
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…