Researchers developed a scalable framework that predicts insulin resistance using wearable-device signals, routine blood biomarkers, and demographic data, with stronger performance when these data streams were combined. The study also introduced an AI agent to explain insulin resistance risk, interpret results, and support earlier metabolic risk screening.
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