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Predicting the naturalistic course of depression from a wide range of clinical, psychological, and biological data: a machine learning approach

Many variables have been linked to different course trajectories of depression. These findings, however, are based on group comparisons with unknown translational value. This study evaluated the prognostic value of a wide range of clinical, psychological, and biological characteristics for predictin...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Veröffentlicht in:Transl Psychiatry
Hauptverfasser: Dinga, Richard, Marquand, Andre F., Veltman, Dick J., Beekman, Aartjan T. F., Schoevers, Robert A., van Hemert, Albert M., Penninx, Brenda W. J. H., Schmaal, Lianne
Format: Artigo
Sprache:Inglês
Veröffentlicht: Nature Publishing Group UK 2018
Schlagworte:
Online Zugang:https://ncbi.nlm.nih.gov/pmc/articles/PMC6218451/
https://ncbi.nlm.nih.gov/pubmed/30397196
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41398-018-0289-1
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