Identification of risk factors for mortality associated with COVID-19.

ABSTRACT:

Objectives

Coronavirus Disease 2019 (COVID-19) has become a pandemic outbreak. Risk stratification at hospital admission is of vital importance for medical decision making and resource allocation. There is no sophisticated tool for this purpose. This study aimed to develop neural network models with predictors selected by genetic algorithms (GA).

Methods

This study was conducted in Wuhan Third Hospital from January 2020 to March 2020. Predictors were collected on day 1 of hospital admission. The primary outcome was the vital status at hospital discharge. Predictors were selected by using GA, and neural network models were built with the cross-validation method. The final neural network models were compared with conventional logistic regression models.

Results

A total

SUBMITTER: Yu Y 

PROVIDER: S-EPMC7473053 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature