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

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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Bibliographic Details
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.
Format: Online
Language:English
Published: 2016
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4935654/

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4935654/

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