Open AccessMachine Learning Algorithms are Superior to Conventional Regression Models in Predicting Risk Stratification of COVID-19 Patients
Author(s) -
Jiru Ye,
Hua Meng,
Feng Zhu
Publication year - 2021
Publication title -
risk management and healthcare policy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.828
H-Index - 22
ISSN - 1179-1594
DOI - 10.2147/rmhp.s318265
Subject(s) - covid-19 , risk stratification , regression , machine learning , artificial intelligence , algorithm , computer science , mathematics , medicine , statistics , infectious disease (medical specialty) , virology , disease , outbreak
It is very important to determine the risk of patients developing severe or critical COVID-19, but most of the existing risk prediction models are established using conventional regression models. We aim to use machine learning algorithms to develop predictive models and compare predictive performance with logistic regression models.