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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...

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Библиографические подробности
Опубликовано в: :Transl Psychiatry
Главные авторы: 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
Формат: Artigo
Язык:Inglês
Опубликовано: Nature Publishing Group UK 2018
Предметы:
Online-ссылка: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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