A machine learning approach for distinguishing age of infants using auditory evoked potentials

Clinical Neurophysiology

Volumn 122, Issue 11, 2011, Pages 2139-2150

  Ravan, Maryam ^a   Reilly, James P ^a   Trainor, Laurel J ^a   Khodayari Rostamabad, Ahmad ^a  

^a MCMASTER UNIVERSITY   (Canada)

Author keywords

Age group determination; Classification; Electroencephalogram (EEG); Event related potentials (ERPs); Feature extraction; Machine learning; Wavelet coefficients

Indexed keywords

ACCURACY; ADULT; ARTICLE; AUDITORY STIMULATION; BRAIN DEVELOPMENT; EVOKED AUDITORY RESPONSE; FEMALE; GROUPS BY AGE; HUMAN; HUMAN EXPERIMENT; INFANT; MACHINE LEARNING; MALE; NORMAL HUMAN; PREDICTION; PRIORITY JOURNAL; RELIABILITY; VALIDATION PROCESS; WAVELET ANALYSIS;

ADULT; AGING; ARTIFICIAL INTELLIGENCE; BRAIN; CHILD DEVELOPMENT; ELECTROENCEPHALOGRAPHY; EVOKED POTENTIALS; EVOKED POTENTIALS, AUDITORY; FEMALE; HUMANS; INFANT; MALE; YOUNG ADULT;

EID: 80053189250     PISSN: 13882457     EISSN: 18728952     Source Type: Journal    
DOI: 10.1016/j.clinph.2011.04.002     Document Type: Article

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