Artificial neural network and logistic regression modelling to characterize COVID-19 infected patients in local areas of Iran.

ABSTRACT:

Background

COVID-19 is an infectious disease that started spreading globally at the end of 2019. Due to differences in patient characteristics and symptoms in different regions, in this research, a comparative study was performed on COVID-19 patients in 6 provinces of Iran. Also, multilayer perceptron (MLP) neural network and Logistic Regression (LR) models were applied for the diagnosis of COVID-19.

Methods

A total of 1043 patients with suspected COVID-19 infection in Iran participated in this study. 29 characteristics, symptoms and underlying disease were obtained from hospitalized patients. Afterwards, we compared the obtained data between confirmed cases. Furthermore, the data was applied for building the ANN and LR models to diagnosis the infected patients by COVID-19.<

SUBMITTER: Mohammadi F 

PROVIDER: S-EPMC7905378 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature