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Stratification of hospitalized COVID-19 patients into clinical severity progression groups by immuno-phenotyping and machine learning
- Source :
- Nature Communications, Vol 13, Iss 1, Pp 1-13 (2022)
- Publication Year :
- 2022
- Publisher :
- Nature Portfolio, 2022.
-
Abstract
- Developing predictive methods to identify patients with high risk of severe COVID-19 disease is of crucial importance. Authors show here that by measuring anti-SARS-CoV-2 antibody and cytokine levels at the time of hospital admission and integrating the data by unsupervised hierarchical clustering/machine learning, it is possible to predict unfavourable outcome.
- Subjects :
- Science
Subjects
Details
- Language :
- English
- ISSN :
- 20411723
- Volume :
- 13
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Nature Communications
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.8868b5c6ee1046f79b63a7f738da79df
- Document Type :
- article
- Full Text :
- https://doi.org/10.1038/s41467-022-28621-0