File:Longitudinal multi-omics and wearable data enabled deep phenotyping for precision health.jpg
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Longitudinal multi-omics and wearable data enabled deep phenotyping for precision health
Summary[edit]
| Description |
English: 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. |
| Date | |
| Source | https://www.mcponline.org/article/S1535-9476(23)00071-3/fulltext |
| Author | Mohan Babu, Michael Snyder |
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| current | 15:56, 8 December 2023 | | 3,322 × 1,709 (834 KB) | DoctorNaturopath (talk | contribs) | Uploaded a work by Mohan Babu, Michael Snyder from https://www.mcponline.org/article/S1535-9476(23)00071-3/fulltext with UploadWizard |
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