Scaling Clinical Judgment to Evaluate Medical AI
Blinded physician evaluation has been considered by many to be the gold standard for assessing clinical reasoning in large language models (LLMs). This is difficult to scale; thus, prior studies typically rely on small physician panels, often from a single institution or specialty, which both limits the scientific questions investigated and makes it unclear whether findings would be reproduced with a different set of evaluators. To more rigorously and scalably study clinical reasoning in AI models, here we introduce PrecepTron, an LLM fine-tuned for physician-level evaluation of open-ended responses. PrecepTron was trained using low-rank adaptation (LoRA) of a 32-billion-parameter model o...
| Authors | Thomas A. Buckley, Zahir Kanjee, Peter G. Brodeur et al. |
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| Primary category | cs.AI |
| Published | 11 September 2026 |
| Last updated at source | 1 October 2026 |
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