Identification of MCI individuals using structural and functional connectivity networks

NeuroImage

Volumn 59, Issue 3, 2012, Pages 2045-2056

  Wee, Chong Yaw ^a   Yap, Pew Thian ^a   Zhang, Daoqiang ^a   Denny, Kevin ^b   Browndyke, Jeffrey N ^b,c   Potter, Guy G ^b   Welsh Bohmer, Kathleen A ^b   Wang, Lihong ^b   Shen, Dinggang ^a  

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

^b DUKE UNIVERSITY MEDICAL CENTER   (United States)

^c DUKE UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

Alzheimer's disease (AD); Brain network analysis multiple kernel Support Vector Machines (SVMs); Diffusion tensor imaging (DTI); Mild cognitive impairment (MCI); Multimodality representation; Resting state functional magnetic resonance imaging (rs fMRI)

Indexed keywords

ADULT; ALZHEIMER DISEASE; ARTICLE; CLINICAL ARTICLE; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DIFFUSION TENSOR IMAGING; DISEASE CLASSIFICATION; FEMALE; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HUMAN; IMAGE ANALYSIS; IMAGE PROCESSING; MALE; MILD COGNITIVE IMPAIRMENT; PRIORITY JOURNAL; RECEIVER OPERATING CHARACTERISTIC; RISK ASSESSMENT; SUPPORT VECTOR MACHINE; SYMPTOM; VALIDATION PROCESS;

AGED; ALGORITHMS; ARTIFICIAL INTELLIGENCE; BRAIN; CLUSTER ANALYSIS; COHORT STUDIES; DATA INTERPRETATION, STATISTICAL; DIFFUSION TENSOR IMAGING; EDUCATIONAL STATUS; FEMALE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; LINEAR MODELS; MAGNETIC RESONANCE IMAGING; MALE; MIDDLE AGED; MILD COGNITIVE IMPAIRMENT; NERVE NET; NEURAL PATHWAYS; NEUROPSYCHOLOGICAL TESTS; NONLINEAR DYNAMICS; REPRODUCIBILITY OF RESULTS; ROC CURVE; SUPPORT VECTOR MACHINES;

EID: 84855453290     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2011.10.015     Document Type: Article

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