Individualized prediction of illness course at the first psychotic episode: a support vector machine MRI study.

Hdl Handle:
http://hdl.handle.net/10147/244207
Title:
Individualized prediction of illness course at the first psychotic episode: a support vector machine MRI study.
Authors:
Mourao-Miranda, J; Reinders, 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.
Citation:
Individualized prediction of illness course at the first psychotic episode: a support vector machine MRI study. 2012, 42 (5):1037-47 Psychol Med
Journal:
Psychological medicine
Issue Date:
May-2012
URI:
http://hdl.handle.net/10147/244207
DOI:
10.1017/S0033291711002005
PubMed ID:
22059690
Additional Links:
http://journals.cambridge.org/download.php?file=%2F25539_0E81A2842381C7988A0DAD68AE8195F9_journals__PSM_PSM42_05_S0033291711002005a.pdf&cover=Y&code=dc5e5e7db712fa74d298f403f4d38dc7; http://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:
Article
Language:
en
MeSH:
Adult; Brain; 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
ISSN:
1469-8978

Full metadata record

DC FieldValue Language
dc.contributor.authorMourao-Miranda, Jen_GB
dc.contributor.authorReinders, A A T Sen_GB
dc.contributor.authorRocha-Rego, Ven_GB
dc.contributor.authorLappin, Jen_GB
dc.contributor.authorRondina, Jen_GB
dc.contributor.authorMorgan, Cen_GB
dc.contributor.authorMorgan, K Den_GB
dc.contributor.authorFearon, Pen_GB
dc.contributor.authorJones, P Ben_GB
dc.contributor.authorDoody, G Aen_GB
dc.contributor.authorMurray, R Men_GB
dc.contributor.authorKapur, Sen_GB
dc.contributor.authorDazzan, Pen_GB
dc.date.accessioned2012-09-17T09:01:15Z-
dc.date.available2012-09-17T09:01:15Z-
dc.date.issued2012-05-
dc.identifier.citationIndividualized prediction of illness course at the first psychotic episode: a support vector machine MRI study. 2012, 42 (5):1037-47 Psychol Meden_GB
dc.identifier.issn1469-8978-
dc.identifier.pmid22059690-
dc.identifier.doi10.1017/S0033291711002005-
dc.identifier.urihttp://hdl.handle.net/10147/244207-
dc.description.abstractTo 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.en_GB
dc.language.isoenen
dc.relation.urlhttp://journals.cambridge.org/download.php?file=%2F25539_0E81A2842381C7988A0DAD68AE8195F9_journals__PSM_PSM42_05_S0033291711002005a.pdf&cover=Y&code=dc5e5e7db712fa74d298f403f4d38dc7en_GB
dc.relation.urlhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC3315786/pdf/S0033291711002005a.pdfen_GB
dc.rightsArchived with thanks to Psychological medicineen_GB
dc.subject.meshAdult-
dc.subject.meshBrain-
dc.subject.meshBrain Mapping-
dc.subject.meshCohort Studies-
dc.subject.meshDisease Progression-
dc.subject.meshFemale-
dc.subject.meshFollow-Up Studies-
dc.subject.meshHumans-
dc.subject.meshImage Processing, Computer-Assisted-
dc.subject.meshIndividuality-
dc.subject.meshMagnetic Resonance Imaging-
dc.subject.meshMale-
dc.subject.meshObserver Variation-
dc.subject.meshPredictive Value of Tests-
dc.subject.meshPsychotic Disorders-
dc.subject.meshReproducibility of Results-
dc.subject.meshSupport Vector Machines-
dc.titleIndividualized prediction of illness course at the first psychotic episode: a support vector machine MRI study.en_GB
dc.typeArticleen
dc.contributor.departmentCentre for Neuroimaging Sciences, Institute of Psychiatry, King's College London, UK.en_GB
dc.identifier.journalPsychological medicineen_GB
dc.description.provinceLeinsteren

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