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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Auteurs principaux: | 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 |
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Format: | article |
Langue: | EN |
Publié: |
Nature Portfolio
2021
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Sujets: | |
Accès en ligne: | https://doaj.org/article/05e8f4be9b9244a0bd5e8c0dcae77ba7 |
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