Novel machine learning methods for ERP analysis: A validation from research on infants at risk for autism

Developmental Neuropsychology

Volumn 37, Issue 3, 2012, Pages 274-298

  Stahl, Daniel ^a   Pickles, Andrew ^a   Elsabbagh, Mayada ^b   Johnson, Mark H ^c  

^a KING'S COLLEGE LONDON   (United Kingdom)

^b MCGILL UNIVERSITY   (Canada)

^c UNIVERSITY OF LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; ARTIFICIAL INTELLIGENCE; ATTENTION; AUTISM; AUTOMATED PATTERN RECOGNITION; DISCRIMINANT ANALYSIS; ELECTROENCEPHALOGRAPHY; EVOKED RESPONSE; EYE FIXATION; HUMAN; INFANT; METHODOLOGY; PATHOPHYSIOLOGY; PHYSIOLOGY; REACTION TIME; REPRODUCIBILITY; RISK; STATISTICAL MODEL;

ARTIFICIAL INTELLIGENCE; ATTENTION; AUTISTIC DISORDER; DISCRIMINANT ANALYSIS; ELECTROENCEPHALOGRAPHY; EVOKED POTENTIALS; FIXATION, OCULAR; HUMANS; INFANT; LOGISTIC MODELS; PATTERN RECOGNITION, AUTOMATED; REACTION TIME; REPRODUCIBILITY OF RESULTS; RISK;

EID: 84862058665     PISSN: 87565641     EISSN: None     Source Type: Journal    
DOI: 10.1080/87565641.2011.650808     Document Type: Article

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