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About this paper
Sarah Montgomery-Taylor, Hamsa Subramaniam, Rob Brisk, Liam Foster, Jack Ching, Andrew Marshall, Jim Taylor, John Hernandez and 25 more
The authors propose a framework for evaluating health AI by starting with a critical user journey, then assessing accuracy, safety, and usefulness through complementary methods across its lifecycle. It maps benchmarks, AI-judge ratings, and expert review to development and monitoring. Their review of over 760 LLM-evaluation papers found disproportionate emphasis on accuracy; the framework itself is not validated.
Summary by alphaXiv.
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