Automatic detection of attention deficit hyperactivity disorder using machine learning algorithms based on short time Fourier transform and discrete cosine transform

OBJECTIVE: Attention deficit hyperactivity disorder (ADHD) is a predominant neurobehavioral illness in minors and adolescents, with overlapping symptoms that complicate established diagnostic approaches. Electroencephalography (EEG) is a noninvasive system for analyzing brain action, with the possibility of automated diagnosis.

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