Predicting lethal courses in critically ill COVID-19 patients using a machine learning model trained on patients with non-COVID-19 viral pneumonia

Predicting lethal courses in critically ill COVID-19 patients using a machine learning model trained on patients with non-COVID-19 viral pneumonia

Abstract In a pandemic with a novel disease, disease-specific prognosis models are available only with a delay. To bridge the critical early phase, models built for similar diseases might be applied. To test the accuracy of such a knowledge transfer, we investigated how precise lethal courses in cri...

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Bibliographic Details
Main Authors: Gregor Lichtner, Felix Balzer, Stefan Haufe, Niklas Giesa, Fridtjof Schiefenhövel, Malte Schmieding, Carlo Jurth, Wolfgang Kopp, Altuna Akalin, Stefan J. Schaller, Steffen Weber-Carstens, Claudia Spies, Falk von Dincklage
Format: Article
Language:English
Published: Nature Publishing Group 2021-06-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-021-92475-7

Internet

https://doi.org/10.1038/s41598-021-92475-7

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