AI RESEARCH
Clinician input steers frontier AI models toward both accurate and harmful decisions
arXiv CS.LG
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ArXi:2603.14158v1 Announce Type: cross Large language models (LLMs) are entering clinician workflows, yet evaluations rarely measure how clinician reasoning shapes model behavior during clinical interactions. We combined 61 New England Journal of Medicine Case Records with 92 real-world clinician-AI interactions to evaluate 21 reasoning LLM variants across 8 frontier models on differential diagnosis generation and next step recommendations under three conditions: reasoning alone, after expert clinician context, and after adversarial clinician context.