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Development and validation of self-monitoring auto-updating prognostic models of survival for hospitalized COVID-19 patients

Authors :
Todd J. Levy
Kevin Coppa
Jinxuan Cang
Douglas P. Barnaby
Marc D. Paradis
Stuart L. Cohen
Alex Makhnevich
David van Klaveren
David M. Kent
Karina W. Davidson
Jamie S. Hirsch
Theodoros P. Zanos
Source :
Nature Communications, Vol 13, Iss 1, Pp 1-14 (2022)
Publication Year :
2022
Publisher :
Nature Portfolio, 2022.

Abstract

Despite rapid and significant changes during the pandemic, prognostic models for COVID-19 patients do not currently account for data drifts. Here, the authors develop a framework for continuously monitoring and updating prognostic models and applied it to predict 28-day survival in COVID-19 patients.

Subjects

Subjects :
Science

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.683b8b5d02ea4901ab5cfc731bf455d7
Document Type :
article
Full Text :
https://doi.org/10.1038/s41467-022-34646-2