| Literature DB >> 27039698 |
George Gifford1, Nicolas Crossley2, Paolo Fusar-Poli2, Hugo G Schnack3, René S Kahn3, Nikolaos Koutsouleris4, Tyrone D Cannon5, Philip McGuire2.
Abstract
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.Entities:
Keywords: Graph analysis; Machine learning; Multicentre neuroimaging studies; Multimodal neuroimaging; Psychosis prediction; Support vector machines; Ultra high-risk of psychosis
Mesh:
Year: 2016 PMID: 27039698 DOI: 10.1016/j.neuroimage.2016.03.075
Source DB: PubMed Journal: Neuroimage ISSN: 1053-8119 Impact factor: 6.556