High Classification Accuracy for Schizophrenia with Rest and Task fMRI Data

We present a novel method to extract classification features from functional magnetic resonance imaging (fMRI) data collected at rest or during the performance of a task. By combining a two-level feature identification scheme with kernel principal component analysis (KPCA) and Fisher’s linear discri...

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Detalles Bibliográficos
Autores principales: Du, Wei, Calhoun, Vince D., Li, Hualiang, Ma, Sai, Eichele, Tom, Kiehl, Kent A., Pearlson, Godfrey D., Adali, Tülay
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Research Foundation 2012
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3366580/
https://www.ncbi.nlm.nih.gov/pubmed/22675292
http://dx.doi.org/10.3389/fnhum.2012.00145

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3366580/
https://www.ncbi.nlm.nih.gov/pubmed/22675292
http://dx.doi.org/10.3389/fnhum.2012.00145

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