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.
Tarek Ahmed Ibrahim Etman (Sun,) studied this question.