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Rohan Paul
@rohanpaul_ai

💊 New study finds that clinical LLMs can ace medical exams yet still perform weakly on realistic clinical tasks and safety. models scored 84%-90% on knowledge exams but only 45%-69% on practice tasks and 40%-50% on safety assessments. The authors analyze 39 benchmarks with about 2.3 million questions across 45 languages and 172 specialties, and see knowledge-style exams largely saturated, with top models near 84%-90% accuracy. On practice-focused benchmarks such as DiagnosisArena, MedAgentBench, and HealthBench, success falls to about 45%-69%, showing that models often fail when asked to pick diagnoses, management plans, or recommendations in full cases. Looking at task types, factual lookup stays near 85%-93%, but clinical reasoning drops to 50%-60%, diagnostic accuracy to 45%-55%, and safety checks reach only 40%-50%. The authors argue that exam-style benchmarks are misleading proxies for clinical readiness and that deployment must rely on practice-based evaluation with strict human-in-the-loop oversight instead of autonomous use. --- pubmed.ncbi. nlm.nih .gov/41325597/

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