Predictive models of resting state networks for assessment of altered functional connectivity in MCI

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 8150 LNCS, Issue PART 2, 2013, Pages 674-681

  Jiang, Xi ^a   Zhu, Dajiang ^a   Li, Kaiming ^b   Zhang, Tuo ^a,c   Shen, Dinggang ^d   Guo, Lei ^c   Liu, Tianming ^a  

^a University of Georgia ^*  (United States)

^b EMORY UNIVERSITY   (United States)

^c NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

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

Author keywords

functional connectivity (FC); mild cognitive impairment (MCI); predictive models; resting state networks

Indexed keywords

BRAIN NETWORKS; FUNCTIONAL CONNECTIVITY; MILD COGNITIVE IMPAIRMENTS (MCI); MULTI-MODAL; NORMAL CONTROLS; PREDICTIVE MODELS; RESTING STATE; RESTING-STATE FMRI;

ARTIFICIAL INTELLIGENCE; COMPUTER SCIENCE;

TENSORS;

ARTICLE; BIOLOGICAL MODEL; BRAIN; BRAIN MAPPING; COMPUTER SIMULATION; CONNECTOME; IMAGE ENHANCEMENT; METHODOLOGY; MILD COGNITIVE IMPAIRMENT; NERVE CELL NETWORK; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOPHYSIOLOGY; REPRODUCIBILITY; REST; SENSITIVITY AND SPECIFICITY;

BRAIN; BRAIN MAPPING; COMPUTER SIMULATION; CONNECTOME; IMAGE ENHANCEMENT; MAGNETIC RESONANCE IMAGING; MILD COGNITIVE IMPAIRMENT; MODELS, NEUROLOGICAL; NERVE NET; REPRODUCIBILITY OF RESULTS; REST; SENSITIVITY AND SPECIFICITY;

EID: 84897577684     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-40763-5_83     Document Type: Conference Paper

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