Predicting individual improvement in schizophrenia symptom severity at 1‐year follow‐up: Comparison of connectomic, structural, and clinical predictors

Volume: 41, Issue: 12, Pages: 3342 - 3357
Published: May 29, 2020
Abstract
In a machine learning setting, this study aims to compare the prognostic utility of connectomic, brain structural, and clinical/demographic predictors of individual change in symptom severity in individuals with schizophrenia. Symptom severity at baseline and 1-year follow-up was assessed in 30 individuals with a schizophrenia-spectrum disorder using the Brief Psychiatric Rating Scale. Structural and functional neuroimaging was acquired in all...
Paper Details
Title
Predicting individual improvement in schizophrenia symptom severity at 1‐year follow‐up: Comparison of connectomic, structural, and clinical predictors
Published Date
May 29, 2020
Volume
41
Issue
12
Pages
3342 - 3357
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.