Canonical feature selection for joint regression and multi-class identification in Alzheimer’s disease diagnosis

Brain Imaging and Behavior

Volumn 10, Issue 3, 2016, Pages 818-828

  Zhu, Xiaofeng ^a   Suk, Heung Il ^b   Lee, Seong Whan ^b   Shen, Dinggang ^a,b  

^a UNIVERSITY OF NORTH CAROLINA SCHOOL OF MEDICINE   (United States)

^b Korea University   (South Korea)

Author keywords

Alzheimer s disease; Canonical correlation analysis; Feature selection; Mild cognitive impairment conversion; Multi class classification

Indexed keywords

ADULT; AGED; ALZHEIMER DISEASE; ARTICLE; CLINICAL DEMENTIA RATING; CORRELATION ANALYSIS; DAILY LIFE ACTIVITY; DIGITAL IMAGING AND COMMUNICATIONS IN MEDICINE; DISEASE CLASSIFICATION; HUMAN; IMAGE ANALYSIS; IMAGE PROCESSING; MAJOR CLINICAL STUDY; MILD COGNITIVE IMPAIRMENT; MINI MENTAL STATE EXAMINATION; NEUROIMAGING; NUCLEAR MAGNETIC RESONANCE IMAGING; POSITRON EMISSION TOMOGRAPHY; PRIORITY JOURNAL; SUPPORT VECTOR MACHINE; ALGORITHM; BRAIN; CLASSIFICATION; DIAGNOSTIC IMAGING; FEMALE; INFORMATION PROCESSING; MALE; MENTAL HEALTH; MIDDLE AGED; NEUROPSYCHOLOGICAL TEST; PATHOPHYSIOLOGY; PROCEDURES; REGRESSION ANALYSIS; VERY ELDERLY;

AGED; AGED, 80 AND OVER; ALGORITHMS; ALZHEIMER DISEASE; BRAIN; DATASETS AS TOPIC; FEMALE; HUMANS; MAGNETIC RESONANCE IMAGING; MALE; MENTAL STATUS SCHEDULE; MIDDLE AGED; NEUROPSYCHOLOGICAL TESTS; POSITRON-EMISSION TOMOGRAPHY; REGRESSION ANALYSIS;

EID: 84938780497     PISSN: 19317557     EISSN: 19317565     Source Type: Journal    
DOI: 10.1007/s11682-015-9430-4     Document Type: Article

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