Use of biochemical tests and machine learning in the search for potential diagnostic biomarkers of COVID-19, HIV/AIDS, and pulmonary tuberculosis

Detalhes bibliográficos
Autor(a) principal: Cobre, Alexandre
Data de Publicação: 2024
Outros Autores: Morais, Amiel, Selege, Fosfato, Stremel, Dile, Wiens, Astrid, Ferreira, Luana, Tonin, Fernanda, Pontarolo, Roberto
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.21/17177
Resumo: The authors express their gratitude to the Brazilian National Council of Technological and Scientific Development (CNPq) and CAPES (Brazilian Federal Agency for Support and Evaluation of Graduate Education within the Ministry of Education of Brazil) for research funding - Finance Code 001.
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spelling Use of biochemical tests and machine learning in the search for potential diagnostic biomarkers of COVID-19, HIV/AIDS, and pulmonary tuberculosisCOVID-19HIV infectionAIDSTuberculosisCo-infectionDiagnosisMachine learningThe authors express their gratitude to the Brazilian National Council of Technological and Scientific Development (CNPq) and CAPES (Brazilian Federal Agency for Support and Evaluation of Graduate Education within the Ministry of Education of Brazil) for research funding - Finance Code 001.This study aims to develop, validate, and evaluate machine learning algorithms for predicting the diagnosis of coronavirus disease (COVID-19), human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS), pulmonary tuberculosis (TB), and HIV/TB co-infection. We also investigated potential biomarkers associated with the diagnosis. Data from biochemical and hematological tests of infected and controls were collected in a single general hospital, totalizing 6,418 patients. The discriminant analysis by partial least squares (PLS-DA) model had the highest performance in predicting the diagnosis of COVID-19, HIV/AIDS, TB, and HIV/TB co-infection with an accuracy of 94, 97, 95, and 96%, respectively. The biomarkers calcium, lactate dehydrogenase, red blood cells (RBC), white blood cells, neutrophils, basophils, eosinophils, hemoglobin, and hematocrit were associated with COVID-19. HIV infection was associated with mean corpuscular volume, platelets, neutrophils, and mean platelet volume. Red blood cell distribution width and urea were associated with infection by Mycobacterium tuberculosis. The following biomarkers were associated with HIV/TB co-infection: lymphocytes, RBC, hematocrit, hemoglobin, aspartate transaminase, alanine transaminase, and glycemia. The PLS-DA model can optimize COVID-19, HIV/AIDS, TB, and HIV/TB co-infection diagnostics. Some biomarkers were potential diagnostic indicators and could be evaluated during the screening of these diseases.UNICAMPRCIPLCobre, AlexandreMorais, AmielSelege, FosfatoStremel, DileWiens, AstridFerreira, LuanaTonin, FernandaPontarolo, Roberto2024-03-05T12:56:32Z2024-022024-02-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.21/17177engCobre AF, Morais AA, Selege F, Stremel DP, Wiens A, Tonin FS, et al. Use of biochemical tests and machine learning in the search for potential diagnostic biomarkers of COVID-19, HIV/AIDS, and pulmonary tuberculosis. J Braz Chem Soc. 2024 February 15. [Early access.]10.21577/0103-5053.20240020info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-13T02:15:40Zoai:repositorio.ipl.pt:10400.21/17177Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:13:29.741540Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Use of biochemical tests and machine learning in the search for potential diagnostic biomarkers of COVID-19, HIV/AIDS, and pulmonary tuberculosis
title Use of biochemical tests and machine learning in the search for potential diagnostic biomarkers of COVID-19, HIV/AIDS, and pulmonary tuberculosis
spellingShingle Use of biochemical tests and machine learning in the search for potential diagnostic biomarkers of COVID-19, HIV/AIDS, and pulmonary tuberculosis
Cobre, Alexandre
COVID-19
HIV infection
AIDS
Tuberculosis
Co-infection
Diagnosis
Machine learning
title_short Use of biochemical tests and machine learning in the search for potential diagnostic biomarkers of COVID-19, HIV/AIDS, and pulmonary tuberculosis
title_full Use of biochemical tests and machine learning in the search for potential diagnostic biomarkers of COVID-19, HIV/AIDS, and pulmonary tuberculosis
title_fullStr Use of biochemical tests and machine learning in the search for potential diagnostic biomarkers of COVID-19, HIV/AIDS, and pulmonary tuberculosis
title_full_unstemmed Use of biochemical tests and machine learning in the search for potential diagnostic biomarkers of COVID-19, HIV/AIDS, and pulmonary tuberculosis
title_sort Use of biochemical tests and machine learning in the search for potential diagnostic biomarkers of COVID-19, HIV/AIDS, and pulmonary tuberculosis
author Cobre, Alexandre
author_facet Cobre, Alexandre
Morais, Amiel
Selege, Fosfato
Stremel, Dile
Wiens, Astrid
Ferreira, Luana
Tonin, Fernanda
Pontarolo, Roberto
author_role author
author2 Morais, Amiel
Selege, Fosfato
Stremel, Dile
Wiens, Astrid
Ferreira, Luana
Tonin, Fernanda
Pontarolo, Roberto
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv RCIPL
dc.contributor.author.fl_str_mv Cobre, Alexandre
Morais, Amiel
Selege, Fosfato
Stremel, Dile
Wiens, Astrid
Ferreira, Luana
Tonin, Fernanda
Pontarolo, Roberto
dc.subject.por.fl_str_mv COVID-19
HIV infection
AIDS
Tuberculosis
Co-infection
Diagnosis
Machine learning
topic COVID-19
HIV infection
AIDS
Tuberculosis
Co-infection
Diagnosis
Machine learning
description The authors express their gratitude to the Brazilian National Council of Technological and Scientific Development (CNPq) and CAPES (Brazilian Federal Agency for Support and Evaluation of Graduate Education within the Ministry of Education of Brazil) for research funding - Finance Code 001.
publishDate 2024
dc.date.none.fl_str_mv 2024-03-05T12:56:32Z
2024-02
2024-02-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.21/17177
url http://hdl.handle.net/10400.21/17177
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Cobre AF, Morais AA, Selege F, Stremel DP, Wiens A, Tonin FS, et al. Use of biochemical tests and machine learning in the search for potential diagnostic biomarkers of COVID-19, HIV/AIDS, and pulmonary tuberculosis. J Braz Chem Soc. 2024 February 15. [Early access.]
10.21577/0103-5053.20240020
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dc.publisher.none.fl_str_mv UNICAMP
publisher.none.fl_str_mv UNICAMP
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