Individualized prediction of illness course at the first psychotic episode: a support vector machine MRI study.
Authors
Mourao-Miranda, JReinders, A A T S
Rocha-Rego, V
Lappin, J
Rondina, J
Morgan, C
Morgan, K D
Fearon, P
Jones, P B
Doody, G A
Murray, R M
Kapur, S
Dazzan, P
Affiliation
Centre for Neuroimaging Sciences, Institute of Psychiatry, King's College London, UK.Issue Date
2012-05MeSH
AdultBrain
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
Metadata
Show full item recordCitation
Individualized prediction of illness course at the first psychotic episode: a support vector machine MRI study. 2012, 42 (5):1037-47 Psychol MedJournal
Psychological medicineDOI
10.1017/S0033291711002005PubMed ID
22059690Additional Links
http://journals.cambridge.org/download.php?file=%2F25539_0E81A2842381C7988A0DAD68AE8195F9_journals__PSM_PSM42_05_S0033291711002005a.pdf&cover=Y&code=dc5e5e7db712fa74d298f403f4d38dc7http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3315786/pdf/S0033291711002005a.pdf
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.Item Type
ArticleLanguage
enISSN
1469-8978ae974a485f413a2113503eed53cd6c53
10.1017/S0033291711002005
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