Individualized prediction of illness course at the first psychotic episode: a support vector machine MRI study

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Abstract

To date, magnetic resonance imaging (MRI) has made little impact on the diagnosis and monitoring of psychoses in individual patients. In this study, we used a support vector machine (SVM) whole-brain classification approach to predict future illness course at the individual level from MRI data obtained at the first psychotic episode.
Original languageEnglish
Pages (from-to)1037-47
Number of pages11
JournalPsychological Medicine
Volume42
Issue number5
DOIs
Publication statusPublished - May 2012

Keywords

  • Adult
  • Brain
  • Brain Mapping
  • Cohort Studies
  • Disease Progression
  • Female
  • Follow-Up Studies
  • Humans
  • Image Processing, Computer-Assisted
  • Individuality
  • Magnetic Resonance Imaging
  • Male
  • Observer Variation
  • Predictive Value of Tests
  • Psychotic Disorders
  • Reproducibility of Results
  • Support Vector Machines

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