Evolution of Clinical Phenotypes of COVID-19 Patients During Intensive Care Treatment: An Unsupervised Machine Learning Analysis

BACKGROUND: Identification of clinical phenotypes in critically ill COVID-19 patients could improve understanding of the disease heterogeneity and enable prognostic and predictive enrichment. However, previous attempts did not take into account temporal dynamics with high granularity. By including t...

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Detalles Bibliográficos
Autores principales: Siepel, Sander, Dam, Tariq A., Fleuren, Lucas M., Girbes, Armand R.J., Hoogendoorn, Mark, Thoral, Patrick J., Elbers, Paul W.G., Bennis, Frank C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2023
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9902809/
https://www.ncbi.nlm.nih.gov/pubmed/36744415
http://dx.doi.org/10.1177/08850666231153393

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9902809/
https://www.ncbi.nlm.nih.gov/pubmed/36744415
http://dx.doi.org/10.1177/08850666231153393

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