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Please use this identifier to cite or link to this item: https://hdl.handle.net/10923/10759
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dc.contributor.authorHEINSFELD, ANIBAL SÓLON-
dc.contributor.authorFRANCO, ALEXANDRE ROSA-
dc.contributor.authorCRADDOCK, R. CAMERON-
dc.contributor.authorAugusto Buchweitz-
dc.contributor.authorMENEGUZZI, FELIPE-
dc.date.accessioned2017-10-11T18:57:54Z-
dc.date.available2017-10-11T18:57:54Z-
dc.date.issued2017-
dc.identifier.issn2213-1582-
dc.identifier.urihttp://hdl.handle.net/10923/10759-
dc.language.isopt_BR-
dc.relation.ispartofNeuroImage-Clinical-
dc.rightsopenAccess-
dc.subjectAprendizado de Máquina (Machine Learning)-
dc.subjectAutismo-
dc.subjectRessonância Magnética Funcional (fMRI)-
dc.subjectResting state-
dc.subjectDeep Learning-
dc.subjectABIDE-
dc.titleIdentification of autism spectrum disorder using deep learning and the ABIDE dataset-
dc.typeArticle-
dc.date.updated2017-10-11T18:57:53Z-
dc.identifier.doiDOI:10.1016/j.nicl.2017.08.017-
dc.jtitleNeuroImage-Clinical-
dc.volume17-
dc.spage16-
dc.epage23-
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