The geometry of clinical labs and wellness states from deeply phenotyped humans
Longitudinal multi-omics measurements are highly valuable in studying heterogeneity in health and disease phenotypes. Here, the authors apply Pareto Task Inference to analyze the clinical lab tests of 3094 individuals and find three wellness states, and one aberrant health state defining this cohort...
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| Autores principales: | , , , , , , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/3bc217cadb6347bdb67f294b25377a9c |
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| Sumario: | Longitudinal multi-omics measurements are highly valuable in studying heterogeneity in health and disease phenotypes. Here, the authors apply Pareto Task Inference to analyze the clinical lab tests of 3094 individuals and find three wellness states, and one aberrant health state defining this cohort. |
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