Unraveling relevant cross-waves pattern drifts in patient-hospital risk factors among hospitalized COVID-19 patients using explainable machine learning methods

Unraveling relevant cross-waves pattern drifts in patient-hospital risk factors among hospitalized COVID-19 patients using explainable machine learning methods

Abstract Background Several studies explored factors related to adverse clinical outcomes among COVID-19 patients but lacked analysis of the impact of the temporal data shifts on the strength of association between different predictors and adverse outcomes. This study aims to evaluate factors relate...

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Main Authors: Fernanda Cristina Barbosa Lana, Carolina Coimbra Marinho, Bruno Barbosa Miranda de Paiva, Lucas Rocha Valle, Guilherme Fonseca do Nascimento, Leonardo Chaves Dutra da Rocha, Marcelo Carneiro, Joanna d‘Arc Lyra Batista, Fernando Anschau, Pedro Gibson Paraiso, Frederico Bartolazzi, Christiane Corrêa Rodrigues Cimini, Alexandre Vargas Schwarzbold, Danyelle Romana Alves Rios, Marcos André Gonçalves, Milena Soriano Marcolino
Format: Article
Language:English
Published: BMC 2025-04-01
Series:BMC Infectious Diseases
Subjects:
COVID-19
Risk factors
Socioeconomic factors
Machine learning
Critical care outcomes
Mortality
Online Access:https://doi.org/10.1186/s12879-025-10766-0
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https://doi.org/10.1186/s12879-025-10766-0

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