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Journal article

Identification of Variable Importance for Predictions of Mortality From COVID-19 Using AI Models for Ontario, Canada

Abstract

The Severe Acute Respiratory Syndrome Coronavirus 2 pandemic has challenged medical systems to the brink of collapse around the globe. In this paper, logistic regression and three other artificial intelligence models (XGBoost, Artificial Neural Network and Random Forest) are described and used to predict mortality risk of individual patients. The database is based on census data for the designated area and co-morbidities obtained using data …

Authors

Snider B; McBean EA; Yawney J; Gadsden SA; Patel B

Journal

Frontiers in Public Health, Vol. 9, ,

Publisher

Frontiers

DOI

10.3389/fpubh.2021.675766

ISSN

2296-2565