A novel multi-relation regularization method for regression and classification in AD diagnosis

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

Volumn 8675 LNCS, Issue PART 3, 2014, Pages 401-408

  Zhu, Xiaofeng ^a   Suk, Heung Il ^a   Shen, Dinggang ^a  

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

Author keywords

Alzheimer's disease; feature selection; manifold learning; MCI conversion; sparse coding

Indexed keywords

FEATURE EXTRACTION; NEURODEGENERATIVE DISEASES; NEUROIMAGING; REGRESSION ANALYSIS;

ALZHEIMER'S DISEASE; MANIFOLD LEARNING; MINI-MENTAL STATE EXAMINATIONS; RECEIVER OPERATING CHARACTERISTIC CURVES; SPARSE CODING; STATE-OF-THE-ART METHODS; SUPPORT VECTOR CLASSIFICATION; SUPPORT VECTOR REGRESSION MODELS;

DIAGNOSIS;

ALGORITHM; ALZHEIMER DISEASE; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; DECISION SUPPORT SYSTEM; HUMAN; METHODOLOGY; MILD COGNITIVE IMPAIRMENT; NEUROPSYCHOLOGICAL TEST; NUCLEAR MAGNETIC RESONANCE IMAGING; POSITRON EMISSION TOMOGRAPHY; REGRESSION ANALYSIS; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; ALZHEIMER DISEASE; ARTIFICIAL INTELLIGENCE; DECISION SUPPORT TECHNIQUES; HUMANS; MAGNETIC RESONANCE IMAGING; MILD COGNITIVE IMPAIRMENT; NEUROPSYCHOLOGICAL TESTS; PATTERN RECOGNITION, AUTOMATED; POSITRON-EMISSION TOMOGRAPHY; REGRESSION ANALYSIS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 84906975457     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-10443-0_51     Document Type: Conference Paper

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