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Importance of immunometabolic markers for the classification of patients with major depressive disorder using machine learning

2022; Elsevier BV; Volume: 121; Linguagem: Inglês

10.1016/j.pnpbp.2022.110674

1878-4216

Yolanda Sánchez‐Carro, Alejandro de la Torre‐Luque, Itziar Leal‐Leturia, Neus Salvat‐Pujol, Clara Massaneda‐Tuneu, Aida de Arriba‐Arnau, Mikel Urretavizcaya, Víctor Pérez, Alba Toll, Antonio Martı́nez-Ruiz, R. Ferreiros-Martinez, Salvador Pérez, Juan Sastre, Pilar Álvarez, Virginia Soria, Pilar López-García,

Cardiac Health and Mental Health

Although there is scientific evidence of the presence of immunometabolic alterations in major depression, not all patients present them. Recent studies point to the association between an inflammatory phenotype and certain clinical symptoms in patients with depression. The objective of our study was to classify major depression disorder patients using supervised learning algorithms or machine learning, based on immunometabolic and oxidative stress biomarkers and lifestyle habits.