33 citations · 51 across the 7 of their papers we have counts for
7 papers
Development, Evaluation, and Deployment of a Multi-Agent System for Thoracic Tumor Board
Tim Ellis-Caleo, Timothy Keyes, Nerissa Ambers +5
Tumor boards are multidisciplinary conferences dedicated to producing actionable patient care recommendations with live review of primary radiology and pathology data. Succinct pat…
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…
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…
Standing on FURM ground -- A framework for evaluating Fair, Useful, and Reliable AI Models in healthcare systems
Alison Callahan, Duncan McElfresh, Juan M. Banda +21
The impact of using artificial intelligence (AI) to guide patient care or operational processes is an interplay of the AI model's output, the decision-making protocol based on that…
Evaluation of GPT-3.5 and GPT-4 for supporting real-world information needs in healthcare delivery
Debadutta Dash, Rahul Thapa, Juan M. Banda +15
Despite growing interest in using large language models (LLMs) in healthcare, current explorations do not assess the real-world utility and safety of LLMs in clinical settings. Our…
DEPLOYR: A technical framework for deploying custom real-time machine learning models into the electronic medical record
Conor K. Corbin, Rob Maclay, Aakash Acharya +6
Machine learning (ML) applications in healthcare are extensively researched, but successful translations to the bedside are scant. Healthcare institutions are establishing framewor…