Using neuroimaging to help predict the onset of psychosis

George Gifford, Nicolas Crossley, Paolo Fusar-Poli, Hugo G. Schnack, René S. Kahn, Nikolaos Koutsouleris, Tyrone D. Cannon, Philip McGuire

Research output: Contribution to journalArticlepeer-review

48 Citations (Scopus)
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The aim of this review is to assess the potential for neuroimaging measures to facilitate prediction of the onset of psychosis. Research in this field has mainly involved people at ‘ultra-high risk’ (UHR) of psychosis, who have a very high risk of developing a psychotic disorder within a few years of presentation to mental health services. The review details the key findings and developments in this area to date, and examines the methodological and logistical challenges associated with making predictions in an individual subject in a clinical setting.
Original languageEnglish
Pages (from-to)209-217
Issue numberPart B
Early online date1 Apr 2016
Publication statusPublished - 15 Jan 2017


  • Psychosis prediction
  • Ultra High-Risk of psychosis
  • machine learning
  • Support Vector Machines
  • multimodal neuroimaging
  • multicentre neuroimaging studies
  • graph analysis


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