Multidimensional Machine Learning for Assessing Parameters Associated With COVID-19 in Vietnam: Validation Study.

ABSTRACT:

Background

Machine learning (ML) is a type of artificial intelligence strategy. Its algorithms are used on big data sets to see patterns, learn from their results, and perform tasks autonomously without being instructed on how to address problems. New diseases like COVID-19 provide important data for ML. Therefore, all relevant parameters should be explicitly quantified and modeled.

Objective

The purpose of this study was to determine (1) the overall preclinical characteristics, (2) the cumulative cutoff values and risk ratios (RRs), and (3) the factors associated with COVID-19 severity in unidimensional and multidimensional analyses involving 2173 SARS-CoV-2 patients.

Methods

The study population consisted of 2173 patients (1587 mild status [mild group] and asymptoma

SUBMITTER: Nguyen TT 

PROVIDER: S-EPMC9937111 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature