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An Interpretable Workflow for Cohort Phenotyping Using Longitudinal Wearable Data.
This work introduces an interpretable workflow for cohort-level phenotyping that leverages longitudinal timestamped wearable metrics, clinically relevant risk strata, and unsupervised machine learning methods to improve transparency and cross-study comparability, supports clinically interpretable subgroup discovery, an...