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PhenoBench: Mapping What a Deeply Phenotyped Human Cohort Can Tell Us
arXiv · AI, language, vision and robotics · article · Sep 5, 2026 · UTC
Deeply phenotyped cohorts combine clinical, imaging, molecular, and wearable observations across timescales from seconds to years, but heterogeneous analyses are not directly comparable. We present PhenoBench, an executable benchmark that turns deep-phenotyping measurements into explicit questions and controlled comparisons of information sources and predictive models. It is built around the Human Phenotype Project, with more than 13,000 participants at the initial visit. Each question fixes the target, population, timing, and allowed information; its evaluation contract specifies the split, m
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First collected: 2026-09-20T21:32:07.623Z. This is not the publication date.
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2026-09-25T18:52:32.462Z
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Deeply phenotyped cohorts combine clinical, imaging, molecular, and wearable observations across timescales from seconds to years. This breadth can reveal which measurements inform which health-related questions, but heterogeneous analyses are not directly comparable. We present PhenoBench, an executable benchmark built around the Human Phenotype Project, in which more than 13,000 participants have completed the initial visit. Each question fixes the target, eligible population, timing, and allowed information; its evaluation contract specifies the split, metric, baseline, and claim boundary. → Deeply phenotyped cohorts combine clinical, imaging, molecular, and wearable observations across timescales from seconds to years, but heterogeneous analyses are not directly comparable. We present PhenoBench, an executable benchmark that turns deep-phenotyping measurements into explicit questions and controlled comparisons of information sources and predictive models. It is built around the Human Phenotype Project, with more than 13,000 participants at the initial visit. Each question fixes the target, population, timing, and allowed information; its evaluation contract specifies the split, m