This note examines benchmark design to evaluate genetic reasoning efficacy in clinical decision-support systems, suggesting implications for deployment.
Clinical decision-support systems increasingly integrate genetic information (variant pathogenicity, gene–disease associations, pharmacogenetics) to guide diagnosis and treatment. This note examines benchmark design for evaluating system performance on genetic reasoning: defining ground-truth variant classifications, constructing curated test cases with known outcomes, and choosing metrics that reflect clinically actionable interpretation accuracy. Rigorous benchmarks reveal system reliability and failure modes before clinical deployment.
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Tarek Ahmed Ibrahim Etman (2026) studied this question.
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