Testing a machine-learning algorithm to predict the persistence and severity of major depressive disorder from baseline self-reports

Heterogeneity of major depressive disorder (MDD) illness course complicates clinical decision-making. While efforts to use symptom profiles or biomarkers to develop clinically useful prognostic subtypes have had limited success, a recent report showed that machine learning (ML) models developed from...

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Detalhes bibliográficos
Publicado no:Mol Psychiatry
Main Authors: Kessler, Ronald C., van Loo, Hanna M., Wardenaar, Klaas J., Bossarte, Robert M., Brenner, Lisa A., Cai, Tianxi, Ebert, David Daniel, Hwang, Irving, Li, Junlong, de Jonge, Peter, Nierenberg, Andrew A., Petukhova, Maria V., Rosellini, Anthony J., Sampson, Nancy A., Schoevers, Robert A., Wilcox, Marsha A., Zaslavsky, Alan M.
Formato: Artigo
Idioma:Inglês
Publicado em: 2016
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Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC4935654/
https://ncbi.nlm.nih.gov/pubmed/26728563
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/mp.2015.198
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