Classification Models for COVID-19 Test Prioritization in Brazil: Machine Learning Approach.

ABSTRACT:

Background

Controlling the COVID-19 outbreak in Brazil is a challenge due to the population's size and urban density, inefficient maintenance of social distancing and testing strategies, and limited availability of testing resources.

Objective

The purpose of this study is to effectively prioritize patients who are symptomatic for testing to assist early COVID-19 detection in Brazil, addressing problems related to inefficient testing and control strategies.

Methods

Raw data from 55,676 Brazilians were preprocessed, and the chi-square test was used to confirm the relevance of the following features: gender, health professional, fever, sore throat, dyspnea, olfactory disorders, cough, coryza, taste disorders, and headache. Classification models were implemented relying o

SUBMITTER: Viana Dos Santos Santana I 

PROVIDER: S-EPMC8034680 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature