Use of Biochemical Tests and Machine Learning in the Search for Potential Diagnostic Biomarkers of COVID-19, HIV/AIDS, and Pulmonary Tuberculosis
Alexandre Cobre,
Amiel Morais,
Fosfato Selege
et al.
Abstract: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 … Show more
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