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...

Description complète

Enregistré dans:
Détails bibliographiques
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
Format: article
Langue:EN
Publié: Nature Portfolio 2021
Sujets:
Accès en ligne:https://doaj.org/article/05e8f4be9b9244a0bd5e8c0dcae77ba7
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires