Application of machine learning algorithms to identify serological predictors of COVID-19 severity and outcomes

Application of machine learning algorithms to identify serological predictors of COVID-19 severity and outcomes

Abstract Background Critically ill hospitalized patients with COVID-19 have greater antibody titers than those with mild to moderate illness, but their association with recovery or death from COVID-19 has not been characterized. Methods In a cohort study of 178 COVID-19 patients, 73 non-hospitalized...

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Main Authors: Santosh Dhakal, Anna Yin, Marta Escarra-Senmarti, Zoe O. Demko, Nora Pisanic, Trevor S. Johnston, Maria Isabel Trejo-Zambrano, Kate Kruczynski, John S. Lee, Justin P. Hardick, Patrick Shea, Janna R. Shapiro, Han-Sol Park, Maclaine A. Parish, Christopher Caputo, Abhinaya Ganesan, Sarika K. Mullapudi, Stephen J. Gould, Michael J. Betenbaugh, Andrew Pekosz, Christopher D. Heaney, Annukka A. R. Antar, Yukari C. Manabe, Andrea L. Cox, Andrew H. Karaba, Felipe Andrade, Scott L. Zeger, Sabra L. Klein
Format: Article
Language:English
Published: Nature Portfolio 2024-11-01
Series:Communications Medicine
Online Access:https://doi.org/10.1038/s43856-024-00658-w
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https://doi.org/10.1038/s43856-024-00658-w

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