Comparing machine learning algorithms for predicting ICU admission and mortality in COVID-19

Comparing machine learning algorithms for predicting ICU admission and mortality in COVID-19

Abstract As predicting the trajectory of COVID-19 is challenging, machine learning models could assist physicians in identifying high-risk individuals. This study compares the performance of 18 machine learning algorithms for predicting ICU admission and mortality among COVID-19 patients. Using COVI...

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Autores principales: Sonu Subudhi, Ashish Verma, Ankit B. Patel, C. Corey Hardin, Melin J. Khandekar, Hang Lee, Dustin McEvoy, Triantafyllos Stylianopoulos, Lance L. Munn, Sayon Dutta, Rakesh K. Jain
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
Materias:
Computer applications to medicine. Medical informatics
R858-859.7
Acceso en línea:https://doaj.org/article/05e8f4be9b9244a0bd5e8c0dcae77ba7
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https://doaj.org/article/05e8f4be9b9244a0bd5e8c0dcae77ba7

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