Predictive classification of individual magnetic resonance imaging scans from children and adolescents.
Neuroimaging techniques are increasingly being explored as potential tools for clinical prediction in psychiatry. There are a wide range of approaches which can be applied to make individual predictions for various aspects of disorders such as diagnostic status, symptom severity scores, identificati...
| Publicado en: | European Child & Adolescent Psychiatry Vol. 22; no. 12; pp. 733 - 745 |
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| Autores principales: | , , , , |
| Formato: | diagnostic images Journal Article |
| Publicado: |
Springer Nature
Dec2013
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104169562&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104169562 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10188827 EJ3 jtl: European Child & Adolescent Psychiatry issn: 10188827 maglogo: N pubinfo: dt: Dec2013 vid: 22 iid: 12 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104169562 92719543 10.1007/s00787-012-0319-0 NLM22930323 104169562 ppf: 733 ppct: 12 formats: fmt: @attributes: type: P tig: atl: Predictive classification of individual magnetic resonance imaging scans from children and adolescents. aug: au: Johnston, B. A. Mwangi, B. Matthews, K. Coghill, D. Steele, J. D. affil: Division of Neuroscience, Ninewells Hospital and Medical School, Medical Research Institute, University of Dundee, Mailbox 5, Dundee, DD1 9SY, UK sug: subj: Magnetic Resonance Imaging Evaluation Neuroradiography Mental Disorders Prognosis Magnetic Resonance Imaging Evaluation Child Adolescence Time Factors Treatment Outcomes Magnetic Resonance Imaging Methods Child: 6-12 years Adolescent: 13-18 years ab: Neuroimaging techniques are increasingly being explored as potential tools for clinical prediction in psychiatry. There are a wide range of approaches which can be applied to make individual predictions for various aspects of disorders such as diagnostic status, symptom severity scores, identification of patients at risk of developing disorders and estimation of the likelihood of response to treatment. This selective review highlights a popular group of pattern recognition techniques, support vector machines (SVMs) for use with structural magnetic resonance imaging scans. First, however, we outline various practical issues, limitations and techniques which need to be considered before SVM’s can be applied. We begin with a discussion on the practicalities of scanning children and adolescent participants and the importance of acquiring high quality images. Scan processing required for inter-subject comparisons is then discussed. We then briefly discuss feature selection and other considerations when applying pattern recognition techniques. Finally, SVMs are described and various studies highlighted to indicate the potential of these techniques for child and adolescent psychiatric research. pubtype: Academic Journal doctype: diagnostic images Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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