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. Although 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 f...

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Veröffentlicht in:Molecular psychiatry 2016-10, Vol.21 (10), p.1366-1371
Hauptverfasser: Kessler, R C, van Loo, H M, Wardenaar, K J, Bossarte, R M, Brenner, L A, Cai, T, Ebert, D D, Hwang, I, Li, J, de Jonge, P, Nierenberg, A A, Petukhova, M V, Rosellini, A J, Sampson, N A, Schoevers, R A, Wilcox, M A, Zaslavsky, A M
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Sprache:eng
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