09/11/26

Scaling clinical judgment to evaluate medical AI.

Buckley, Thomas A; Kanjee, Zahir; Brodeur, Peter G; Crowe, Byron; Pettinato, Anthony M; Shah, Aashna P; Haimovich, Adrian D.; McCoy, Liam G; Restrepo, Daniel; Goh, Ethan; Chen, Jonathan H; Zwaan, Laura; Goodman, Katherine E; Morgan, Daniel J; Abdulnour, Raja-Elie E; Rodman, Adam; Manrai, Arjun K. arXiv

Summary

Physician review of clinical reasoning is essential for evaluating medical AI but difficult to scale. This preprint introduces an LLM evaluator and physician-annotated benchmark. Despite limited examples, this study finds that conventional LLM judges often disagree with physicians, while the tested evaluator more closely matches physician scores across clinical-AI tasks, including stepwise diagnosis as case details arrived. The authors have made the code and data for the tools freely available.
Buckley TA, Kanjee Z, Brodeur PG, et al. Scaling clinical judgment to evaluate medical AI. arXiv. Epub 2026 Sep 11.