Machine learning approach for classification of ADHD adults.

@article{Tenev2014MachineLA,
  title={Machine learning approach for classification of ADHD adults.},
  author={Aleksandar Tenev and Silvana Markovska-Simoska and Ljupco Kocarev and J. Pop-Jordanov and Andreas M{\"u}ller and Gian Candrian},
  journal={International journal of psychophysiology : official journal of the International Organization of Psychophysiology},
  year={2014},
  volume={93 1},
  pages={
          162-6
        }
}
Machine learning techniques that combine multiple classifiers are introduced for classifying adult attention deficit hyperactivity disorder (ADHD) subtypes based on power spectra of EEG measurements. The analyzed sample includes 117 adults (67 ADHD, 50 controls). The measurements are taken for four different conditions: two resting conditions (eyes open and eyes closed) and two neuropsychological tasks (visual continuous performance test and emotional continuous performance test). We divide the… CONTINUE READING
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