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 |
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Hauptverfasser: | , , , , , , , , , , , , , , , , |
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Sprache: | eng |
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