Separating generalized anxiety disorder from major depression using clinical, hormonal, and structural MRI data: A multimodal machine learning study.

Journal: Brain and behavior
Published Date: Mar 1, 2017

Abstract

BACKGROUND: Generalized anxiety disorder (GAD) is difficult to recognize and hard to separate from major depression (MD) in clinical settings. Biomarkers might support diagnostic decisions. This study used machine learning on multimodal biobehavioral data from a sample of GAD, MD and healthy subjects to differentiate subjects with a disorder from healthy subjects (case-classification) and to differentiate GAD from MD (disorder-classification).

Authors

  • Kevin Hilbert
  • Ulrike Lueken
    Department of Psychology, Institute of Clinical Psychology and Psychotherapy, Technische Universität Dresden, Chemnitzer Straße 46, 01187, Dresden, Germany, ulrike.lueken@tu-dresden.de.
  • Markus Muehlhan
    Institute of Clinical Psychology and Psychotherapy Technische Universität Dresden Dresden Germany; Department of Psychology Neuroimaging Center Technische Universität Dresden Dresden Germany.
  • Katja Beesdo-Baum
    Institute of Clinical Psychology and Psychotherapy Technische Universität Dresden Dresden Germany; Behavioral Epidemiology Technische Universität Dresden Dresden Germany; Department of Psychology Neuroimaging CenterTechnische Universität Dresden Dresden Germany.

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