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...

Description complète

Enregistré dans:
Détails bibliographiques
Auteurs principaux: 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
Langue:EN
Publié: Nature Portfolio 2021
Sujets:
R
Q
Accès en ligne:https://doaj.org/article/9f0925fd5b874cefbef161561d71441b
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!