Characterization of groups using composite kernels and multi-source fMRI analysis data: Application to schizophrenia

NeuroImage

Volumn 58, Issue 2, 2011, Pages 526-536

  Castro, Eduardo ^a   Martínez Ramón, Manel ^a,c   Pearlson, Godfrey ^d,e   Sui, Jing ^b   Calhoun, Vince D ^a,b,e  

^a University of New Mexico   (United States)

^b MIND RESEARCH NETWORK   (United States)

^c UNIVERSIDAD CARLOS III DE MADRID   (Spain)

^d INSTITUTE OF LIVING   (United States)

^e YALE UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

Composite kernels; Feature selection; FMRI; Independent component analysis; Pattern classification; Recursive feature elimination; Schizophrenia; Support vector machines

Indexed keywords

ACCURACY; ADULT; ARTICLE; CLASSIFIER; CONTROLLED STUDY; FEMALE; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HUMAN; INDEPENDENT COMPONENT ANALYSIS; INFORMATION PROCESSING; KERNEL METHOD; MAJOR CLINICAL STUDY; MALE; PRIORITY JOURNAL; SCHIZOPHRENIA; STATISTICAL MODEL; TEMPORAL LOBE;

ADOLESCENT; ADULT; AGED; ALGORITHMS; ARTIFICIAL INTELLIGENCE; AUDITORY PERCEPTION; BRAIN MAPPING; DATA INTERPRETATION, STATISTICAL; FEMALE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; LINEAR MODELS; MAGNETIC RESONANCE IMAGING; MALE; MIDDLE AGED; PRINCIPAL COMPONENT ANALYSIS; REPRODUCIBILITY OF RESULTS; SCHIZOPHRENIA; YOUNG ADULT;

EID: 80051781186     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2011.06.044     Document Type: Article

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