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

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 critically i...

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Detalles Bibliográficos
Autores principales: Lichtner, Gregor, Balzer, Felix, Haufe, Stefan, Giesa, Niklas, Schiefenhövel, Fridtjof, Schmieding, Malte, Jurth, Carlo, Kopp, Wolfgang, Akalin, Altuna, Schaller, Stefan J., Weber-Carstens, Steffen, Spies, Claudia, von Dincklage, Falk
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8225662/
https://www.ncbi.nlm.nih.gov/pubmed/34168198
http://dx.doi.org/10.1038/s41598-021-92475-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8225662/
https://www.ncbi.nlm.nih.gov/pubmed/34168198
http://dx.doi.org/10.1038/s41598-021-92475-7

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