Using neuroimaging to help predict the onset of psychosis

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• 作者：George Gifford^a ; ^{george.gifford@kcl.ac.uk} ; Nicolas Crossley^a ; Paolo Fusar-Poli^a ; Hugo G. Schnack^b ; René ; S. Kahn^b ; Nikolaos Koutsouleris^c ; Tyrone D. Cannon^d ; ^e ; Philip McGuire^a
• 关键词：Psychosis prediction ; Ultra high-risk of psychosis ; Machine learning ; Support vector machines ; Multimodal neuroimaging ; Multicentre neuroimaging studies ; Graph analysis
• 刊名：NeuroImage
• 出版年：2017
• 出版时间：15 January 2017
• 年：2017
• 卷：145
• 期：part_PB
• 页码：209-217
• 全文大小：917 K
• 卷排序：145

文摘

Machine learning methods allow for prediction of psychosis outcomes in individuals. Current multicentre studies seek to recruit sufficient samples for ML prediction. Multiple modalities can be incorporated into ML predictive models. ML methods can be used to predict continuous outcomes. ML can incorporate graph analysis if data is transformed into vector space.