An integrated feature ranking and selection framework for ADHD characterization

Brain Informatics

Volumn 3, Issue 3, 2016, Pages 145-155

  Xiao, Cao ^a   Bledsoe, Jesse ^a   Wang, Shouyi ^b   Chaovalitwongse, Wanpracha Art ^a   Mehta, Sonya ^a   Semrud Clikeman, Margaret ^c   Grabowski, Thomas ^a  

^a UNIVERSITY OF WASHINGTON   (United States)

^b UNIVERSITY OF TEXAS AT ARLINGTON   (United States)

^c UNIVERSITY OF MINNESOTA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BRAIN; FUNCTIONAL NEUROIMAGING; INFORMATION THEORY; LEARNING ALGORITHMS; LEARNING SYSTEMS; MAGNETIC RESONANCE IMAGING;

ATTENTION DEFICIT HYPERACTIVITY DISORDER; FUNCTIONAL CHARACTERISTICS; FUNCTIONAL CONNECTIVITY; HIGHER DIMENSIONAL FEATURES; INFORMATION THEORETIC CRITERION; LEAST ABSOLUTE SHRINKAGE AND SELECTION OPERATORS; MACHINE LEARNING TECHNIQUES; MAGNETIC RESONANCE IMAGING (MRI);

FEATURE EXTRACTION;

ALGORITHM; ARTICLE; ATTENTION DEFICIT DISORDER; BLOOD OXYGENATION; BRAIN ATROPHY; BRAIN FUNCTION; BRAIN SIZE; CLINICAL EVALUATION; CLINICAL FEATURE; CONNECTOME; CORTICAL THICKNESS (BRAIN); DISEASE ASSESSMENT; DOPAMINERGIC SYSTEM; ELECTROENCEPHALOGRAPHY; FEATURE RANKING; HUMAN; INFORMATION PROCESSING; MACHINE LEARNING; MATHEMATICAL MODEL; NEUROIMAGING; NUCLEAR MAGNETIC RESONANCE IMAGING; POSITIVE FEEDBACK; PREDICTIVE VALUE; PRIORITY JOURNAL; SUPPORT VECTOR MACHINE;

EID: 85018254772     PISSN: 21984018     EISSN: 21984026     Source Type: Journal    
DOI: 10.1007/s40708-016-0047-1     Document Type: Article

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