Restricted Boltzmann machines for neuroimaging: An application in identifying intrinsic networks

NeuroImage

Volumn 96, Issue , 2014, Pages 245-260

  Hjelm, R Devon ^a,b   Calhoun, Vince D ^a,b   Salakhutdinov, Ruslan ^c   Allen, Elena A ^a,e   Adali, Tulay ^d   Plis, Sergey M ^a  

^a MIND RESEARCH NETWORK   (United States)

^b University of New Mexico   (United States)

^c UNIVERSITY OF TORONTO   (Canada)

^d UNIVERSITY OF MARYLAND BALTIMORE COUNTY   (United States)

^e UNIVERSITY OF BERGEN   (Norway)

Author keywords

DBN; FMRI; ICA; Intrinsic networks; RBM

Indexed keywords

ACCURACY; ARTICLE; CONTROLLED STUDY; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HUMAN; INTERMETHOD COMPARISON; INTRINSIC NETWORK; LINEAR SYSTEM; MATHEMATICAL MODEL; NERVE CELL NETWORK; NEUROIMAGING; PRIORITY JOURNAL; PROBABILITY; RESTRICTED BOLTZMANN MACHINE; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; BRAIN; BRAIN MAPPING; COMPUTER ASSISTED DIAGNOSIS; FEMALE; NUCLEAR MAGNETIC RESONANCE IMAGING; PHYSIOLOGY; PROCEDURES; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL ANALYSIS; STATISTICS; YOUNG ADULT;

BRAIN; BRAIN MAPPING; DATA INTERPRETATION, STATISTICAL; FEMALE; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; NERVE NET; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; STOCHASTIC PROCESSES; YOUNG ADULT;

EID: 84899931628     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2014.03.048     Document Type: Article

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