Maximum-uncertainty linear discrimination analysis of first-episode schizophrenia subjects

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dc.contributor.authorKasparek T.
dc.contributor.authorThomaz C.E.
dc.contributor.authorSato J.R.
dc.contributor.authorSchwarz D.
dc.contributor.authorJanousova E.
dc.contributor.authorMarecek R.
dc.contributor.authorPrikryl R.
dc.contributor.authorVanicek J.
dc.contributor.authorFujita A.
dc.contributor.authorCeskova E.
dc.date.accessioned2019-08-19T23:45:22Z
dc.date.available2019-08-19T23:45:22Z
dc.date.issued2011
dc.description.abstractRecent techniques of image analysis brought the possibility to recognize subjects based on discriminative image features. We performed a magnetic resonance imaging (MRI)-based classification study to assess its usefulness for outcome prediction of first-episode schizophrenia patients (FES). We included 39 FES patients and 39 healthy controls (HC) and performed the maximum-uncertainty linear discrimination analysis (MLDA) of MRI brain intensity images. The classification accuracy index (CA) was correlated with the Positive and Negative Syndrome Scale (PANSS) and the Global Assessment of Functioning scale (GAF) at 1-year follow-up. The rate of correct classifications of patients with poor and good outcomes was analyzed using chi-square tests. MLDA classification was significantly better than classification by chance. Leave-one-out accuracy was 72%. CA correlated significantly with PANSS and GAF scores at the 1-year follow-up. Moreover, significantly more patients with poor outcome than those with good outcome were classified correctly. MLDA of brain MR intensity features is, therefore, able to correctly classify a significant number of FES patients, and the discriminative features are clinically relevant for clinical presentation 1 year after the first episode of schizophrenia. The accuracy of the current approach is, however, insufficient to be used in clinical practice immediately. Several methodological issues need to be addressed to increase the usefulness of this classification approach. © 2010 Elsevier Ireland Ltd.
dc.description.firstpage174
dc.description.issuenumber3
dc.description.lastpage181
dc.description.volume191
dc.identifier.citationKasparek, Tomas; Ceskova, Eva; THOMAZ, C. E.; Sato, Joao Ricardo; Schwarz, Daniel; Janousova, Eva; Marecek, Radek; Prikryl, Radovan; Vanicek, Jiri; Fujita, Andre. Maximum-uncertainty linear discrimination analysis of first-episode schizophrenia subjects. Psychiatry Research. Neuroimaging (Print), v. 191, n. 3, p. 174-181, 2011.
dc.identifier.doi10.1016/j.pscychresns.2010.09.016
dc.identifier.issn0925-4927
dc.identifier.urihttps://repositorio.fei.edu.br/handle/FEI/1245
dc.relation.ispartofPsychiatry Research - Neuroimaging
dc.rightsAcesso Restrito
dc.subject.otherlanguageBrain morphology
dc.subject.otherlanguageClassification
dc.subject.otherlanguageFirst episode
dc.subject.otherlanguageSchizophrenia
dc.titleMaximum-uncertainty linear discrimination analysis of first-episode schizophrenia subjects
dc.typeArtigo
fei.scopus.citations39
fei.scopus.eid2-s2.0-79951853456
fei.scopus.updated2024-03-04
fei.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=79951853456&origin=inward
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