Stratification of hospitalized COVID-19 patients into clinical severity progression groups by immuno-phenotyping and machine learning

Quantitative or qualitative differences in immunity may drive clinical severity in COVID-19. Although longitudinal studies to record the course of immunological changes are ample, they do not necessarily predict clinical progression at the time of hospital admission. Here we show, by a machine learn...

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Detalles Bibliográficos
Autores principales: Mueller, Yvonne M., Schrama, Thijs J., Ruijten, Rik, Schreurs, Marco W. J., Grashof, Dwin G. B., van de Werken, Harmen J. G., Lasinio, Giovanna Jona, Álvarez-Sierra, Daniel, Kiernan, Caoimhe H., Castro Eiro, Melisa D., van Meurs, Marjan, Brouwers-Haspels, Inge, Zhao, Manzhi, Li, Ling, de Wit, Harm, Ouzounis, Christos A., Wilmsen, Merel E. P., Alofs, Tessa M., Laport, Danique A., van Wees, Tamara, Kraker, Geoffrey, Jaimes, Maria C., Van Bockstael, Sebastiaan, Hernández-González, Manuel, Rokx, Casper, Rijnders, Bart J. A., Pujol-Borrell, Ricardo, Katsikis, Peter D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8854670/
https://www.ncbi.nlm.nih.gov/pubmed/35177626
http://dx.doi.org/10.1038/s41467-022-28621-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8854670/
https://www.ncbi.nlm.nih.gov/pubmed/35177626
http://dx.doi.org/10.1038/s41467-022-28621-0

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