Using neuroimaging to help predict the onset of psychosis
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Publication date
2017-01
Authors
Gifford, George
Crossley, Nicolas
Fusar-Poli, Paolo
Schnack, H.
Kahn, René S.
Koutsouleris, Nikolaos
Cannon, Tyrone D.
McGuire, Philip
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Document Type
Article
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taverne
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.
Keywords
Graph analysis, Machine learning, Multicentre neuroimaging studies, Multimodal neuroimaging, Psychosis prediction, Support vector machines, Ultra high-risk of psychosis, Taverne, Cognitive Neuroscience, Neurology, Journal Article
Citation
Gifford, G, Crossley, N, Fusar-Poli, P, Schnack, H G, Kahn, R S, Koutsouleris, N, Cannon, T D & McGuire, P 2017, 'Using neuroimaging to help predict the onset of psychosis', NeuroImage, vol. 145, no. Part B, pp. 209-217. https://doi.org/10.1016/j.neuroimage.2016.03.075