Precision Evidence Bench: Assessing PICO alignment and faithful reporting in clinical AI

Clinicians routinely make decisions for patients whose comorbidities, prior therapies, laboratory abnormalities, or demographic characteristics are not reflected in the supporting evidence, even though these factors can influence treatment selection. Given this gap in the evidence base, we sought to evaluate how AI models respond to clinical questions in which patient characteristics or the treatment comparison and outcome of interest may affect the applicability of available evidence. We developed and publicly released Precision Evidence Bench, a benchmark of 209 synthetic clinical questions

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