Journal article

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

Richard Dinga, Andre F Marquand, Dick J Veltman, Aartjan TF Beekman, Robert A Schoevers, Albert M van Hemert, Brenda WJH Penninx, Lianne Schmaal

Translational Psychiatry | NATURE PUBLISHING GROUP | Published : 2018

Grants

Awarded by Geestkracht program of the Netherlands Organization for Health Research and Development (Zon-Mw)


Awarded by Neuroscience Amsterdam


Awarded by Netherlands Brain Foundation


Awarded by NWO under a VIDI fellowship


Funding Acknowledgements

This work was supported by the Geestkracht program of the Netherlands Organization for Health Research and Development (Zon-Mw, grant number 10-000-1002) and is also supported by participating universities and mental health care organizations (VU University Medical Center, GGZ inGeest, Arkin, Leiden University Medical Center, GGZ Rivierduinen, University Medical Center Groningen, Lentis, GGZ Friesland, GGZ Drenthe, Institute for Quality of Health Care (IQ Healthcare), Netherlands Institute for Health Services Research (NIVEL), and Netherlands Institute of Mental Health and Addiction (Trimbos). This work was also supported by Neuroscience Amsterdam (PoC-2014-NMH-02). L.S. and R.D. are supported by the Netherlands Brain Foundation grant number (F2014(1)-24). A.F.M. gratefully acknowledges support from the NWO under a VIDI fellowship (grant number 016.156.415)