Identification of predictive patient characteristics for assessing the probability of COVID-19 in-hospital mortality

As the world emerges from the COVID-19 pandemic, there is an urgent need to understand patient factors that may be used to predict the occurrence of severe cases and patient mortality. Approximately 20% of SARS-CoV-2 infections lead to acute respiratory distress syndrome caused by the harmful action...

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Bibliographic Details
Published in:	PLOS digital health Vol. 3; no. 4; p. e0000327
Main Authors:	Rajwa, Bartek, Naved, Md Mobasshir Arshed, Adibuzzaman, Mohammad, Grama, Ananth Y., Khan, Babar A., Dundar, M. Murat, Rochet, Jean-Christophe
Format:	Journal Article
Language:	English
Published:	United States Public Library of Science 01.04.2024 Public Library of Science (PLoS)
Subjects:	Biology and life sciences Cognitive ability Computer and Information Sciences COVID-19 Cytokine storm Delirium Electronic health records Feature selection Generalized linear models Hospitals Hypotheses Infections Machine learning Medicine and Health Sciences Mortality Pandemics Patients Regression analysis Severe acute respiratory syndrome coronavirus 2 United States > US Indianapolis Indiana
ISSN:	2767-3170, 2767-3170
Online Access:	Get full text
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