Brain connectivity and novel network measures for Alzheimer's disease classification

Neurobiology of Aging

Volumn 36, Issue S1, 2015, Pages S121-S131

  Prasad, Gautam ^a   Joshi, Shantanu H ^a   Nir, Talia M ^a   Toga, Arthur W ^a   Thompson, Paul M ^a,b  

^a UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Alzheimer's disease; Classification; Connectivity matrix; Graph; Maximum flow; Network measures; Ranking; Sensitivity; Specificity; SVM

Indexed keywords

AGED; ALZHEIMER DISEASE; ARTICLE; CLASSIFIER; CONNECTOME; CONTROLLED STUDY; DIAGNOSTIC TEST ACCURACY STUDY; DIFFUSION WEIGHTED IMAGING; DISEASE CLASSIFICATION; FEMALE; HUMAN; IMAGE PROCESSING; LEARNING ALGORITHM; MAJOR CLINICAL STUDY; MALE; MILD COGNITIVE IMPAIRMENT; NERVE CELL NETWORK; NEUROANATOMY; NUCLEAR MAGNETIC RESONANCE SCANNER; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINE; THREE DIMENSIONAL IMAGING; TRACTOGRAPHY; BRAIN; CLASSIFICATION; DIFFERENTIAL DIAGNOSIS; NEUROIMAGING; PATHOLOGY; PATHOPHYSIOLOGY; PROCEDURES; VERY ELDERLY;

AGED; AGED, 80 AND OVER; ALZHEIMER DISEASE; BRAIN; DIAGNOSIS, DIFFERENTIAL; DIFFUSION MAGNETIC RESONANCE IMAGING; FEMALE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MALE; MILD COGNITIVE IMPAIRMENT; NERVE NET; NEUROIMAGING;

EID: 84916608445     PISSN: 01974580     EISSN: 15581497     Source Type: Journal    
DOI: 10.1016/j.neurobiolaging.2014.04.037     Document Type: Article

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