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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Auteurs principaux: | , , , , , , , , , , , , |
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Format: | article |
Langue: | EN |
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Nature Portfolio
2021
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Accès en ligne: | https://doaj.org/article/9f0925fd5b874cefbef161561d71441b |
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