Summary
Claims about LLM diagnostic reasoning depend partly on whether models have encountered similar cases during training. This study compared five frontier LLMs on 2,000 clinical case reports from before and after presumed training cutoffs. Diagnostic accuracy was nearly identical between cohorts, with little lexical or semantic overlap. However, the evaluation relied partly on an AI judge, limiting how conclusively the findings establish “reasoning.”
Sheppert AP, Adams B, Sheppert AD, et al. Reasoning or reciting? A temporal contamination audit of large language models in clinical medicine. J Am Med Inform Assoc. 2026;33(9):1617-1626.