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A multiple kernel learning approach to perform classification of groups from complex-valued fMRI data analysis: application to schizophrenia.

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第一作者： Eduardo,Castro

第一单位： Department of Electrical and Computer Engineering, The University of New Mexico, Albuquerque, NM, USA. Electronic address: ecastrow@unm.edu.

作者： Eduardo,Castro ^[1] ; Vanessa,Gómez-Verdejo ^[2] ; Manel,Martínez-Ramón ^[3] ; Kent A,Kiehl ^[4] ; Vince D,Calhoun ^[5]

作者单位： Department of Electrical and Computer Engineering, The University of New Mexico, Albuquerque, NM, USA. Electronic address: ecastrow@unm.edu. ^[1] Department of Signal Theory and Communications, Universidad Carlos III de Madrid, Madrid, Spain. ^[2] Department of Electrical and Computer Engineering, The University of New Mexico, Albuquerque, NM, USA; Department of Signal Theory and Communications, Universidad Carlos III de Madrid, Madrid, Spain. ^[3] The Mind Research Network, Albuquerque, NM, USA; Department of Psychology, The University of New Mexico, Albuquerque, NM, USA. ^[4] Department of Electrical and Computer Engineering, The University of New Mexico, Albuquerque, NM, USA; The Mind Research Network, Albuquerque, NM, USA. ^[5]

关键词 Complex-valued fMRI data Feature selection Independent component analysis Multiple kernel learning Schizophrenia Support vector machines