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Using Unsupervised Machine Learning to Identify Age- and Sex-Independent Severity Subgroups Among Patients with COVID-19: Observational Longitudinal Study
BACKGROUND: Early detection and intervention are the key factors for improving outcomes in patients with COVID-19. OBJECTIVE: The objective of this observational longitudinal study was to identify nonoverlapping severity subgroups (ie, clusters) among patients with COVID-19, based exclusively on cli...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
JMIR Publications
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8163491/ https://www.ncbi.nlm.nih.gov/pubmed/33872186 http://dx.doi.org/10.2196/25988 |