Predicting the naturalistic course of depression from a wide range of clinical, psychological, and biological data: a machine learning approach (Q58612525)

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scientific article published on 05 November 2018

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English	Predicting the naturalistic course of depression from a wide range of clinical, psychological, and biological data: a machine learning approach	scientific article published on 05 November 2018

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2 May 2020

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

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2 May 2020

biological psychiatry

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machine learning

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2 May 2020

Aartjan T.F. Beekman

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Aartjan T F Beekman

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Brenda W J H Penninx

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Richard Dinga

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2 May 2020

Andre F Marquand

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Dick J Veltman

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2 May 2020

Robert A Schoevers

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2 May 2020

Albert M van Hemert

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5 November 2018

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Translational Psychiatry

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2 May 2020

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2 May 2020

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2 May 2020

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5 November 2018

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Assessing and tuning brain decoders: Cross-validation, caveats, and guidelines

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External validation of the international risk prediction algorithm for major depressive episode in the US general population: the PredictD-US study.

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Cross-trial prediction of treatment outcome in depression: a machine learning approach

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

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30 November 2018

Predicting the Naturalistic Course of Major Depressive Disorder Using Clinical and Multimodal Neuroimaging Information: A Multivariate Pattern Recognition Study

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Low serum BDNF levels in depressed patients cannot be attributed to individual depressive symptoms or symptom cluster

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The association between low vitamin D and depressive disorders

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30 November 2018

Salivary cortisol levels and the 2-year course of depressive and anxiety disorders

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Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010

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Evidence for a differential role of HPA-axis function, inflammation and metabolic syndrome in melancholic versus atypical depression

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Why has it taken so long for biological psychiatry to develop clinical tests and what to do about it?

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Course trajectories of unipolar depressive disorders identified by latent class growth analysis

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30 November 2018

Functional Biomarkers of Depression: Diagnosis, Treatment, and Pathophysiology

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30 November 2018

Metabolic depression: a chronic depressive subtype? Findings from the InCHIANTI study of older persons.

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30 November 2018

Two-year course of depressive and anxiety disorders: results from the Netherlands Study of Depression and Anxiety (NESDA).

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30 November 2018

Psychological characteristics of chronic depression: a longitudinal cohort study

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Serum brain-derived neurotrophic factor in bipolar and unipolar depression: a potential adjunctive tool for differential diagnosis

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Development and validation of an international risk prediction algorithm for episodes of major depression in general practice attendees: the PredictD study

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10.1038/S41398-018-0289-1

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2 May 2020

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