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A Proposed Rubric for Evaluating Expressed Clinical Reasoning in Large Language Model Responses

Jiang, Zhangshu Joshua et al.
arXiv (All) · Papers
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artificial-intelligencecomputation-and-language
We propose a rubric for assessing expressed clinical reasoning in model responses, drawing on three bodies of work: medical education assessment frameworks (ART, SCT, Key Feature Problems and OSCE); clinical LLM benchmarks (MedR-Bench, HealthBench, TIMER-Bench, DR.BENCH, PrIME-LLM and PatientSafeBen
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