Creating multimodal predictors using missing data: Classifying and subtyping autism spectrum disorder

Journal of Neuroscience Methods

Volumn 235, Issue , 2014, Pages 1-9

  Ingalhalikar, Madhura ^a   Parker, William A ^a   Bloy, Luke ^b   Roberts, Timothy P L ^b   Verma, Ragini ^a  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

^b CHILDREN S HOSPITAL OF PHILADELPHIA   (United States)

Author keywords

Autism spectrum disorder; Diffusion tensor imaging; Language impairment; Magnetoencephalography; Missing data; Pattern classification

Indexed keywords

ARTICLE; AUTISM; CLASSIFIER; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DIFFUSION TENSOR IMAGING; DISEASE CLASSIFICATION; DISEASE SEVERITY; LANGUAGE; LANGUAGE DISABILITY; MAGNETOENCEPHALOGRAPHY; PHENOTYPE; PRIORITY JOURNAL; WHITE MATTER; AUTOMATED PATTERN RECOGNITION; BRAIN; CHILD; CHILD DEVELOPMENT DISORDERS, PERVASIVE; CLASSIFICATION; HEARING; HUMAN; PATHOLOGY; PATHOPHYSIOLOGY; PHYSIOLOGY; PROBABILITY; PROCEDURES; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING;

AUDITORY PERCEPTION; BRAIN; CHILD; CHILD DEVELOPMENT DISORDERS, PERVASIVE; DIFFUSION TENSOR IMAGING; HUMANS; MAGNETOENCEPHALOGRAPHY; PATTERN RECOGNITION, AUTOMATED; PROBABILITY; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED; WHITE MATTER;

EID: 84904121707     PISSN: 01650270     EISSN: 1872678X     Source Type: Journal    
DOI: 10.1016/j.jneumeth.2014.06.030     Document Type: Article

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