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Longitudinal multi-omics and wearable data enabled deep phenotyping for precision health. Omics and non-omics data across times (T1-Tn) could be integrated using machine learning and deep learning approaches to predict disease risk, subtyping, biomarker discovery, molecular insights, and response to treatment among others. Figure was created using Biorender (https://biorender.com/).
