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CIU Lecturers explained that with the Use of Artificial Intelligence, the Possibility of Incorrect Diagnosis about Attention Deficit and Hyperactivity Disorder was released

Assist. Prof. Dr. Hüseyin Öztoprak, Lecturer of the Faculty of Engineering and Assoc. Prof. Dr. Mehmet Toycan, Rector’s Advisor noted that the use of electric waves measured by EEG prevents the possibility of misdiagnosis for children with attention deficit and hyperactivity impairment.

Assist. Prof. Dr. Hüseyin Öztoprak emphasized the importance of the views of the family and the teacher on the child during the diagnosis phase of the children with attention deficit and hyperactivity disorder within the scope of the project. Öztoprak said that there is no hyperactivity disorder in every active child and he explained as a result of such misjudgement of family or teacher, children without hyperactivity impairment were sent to psychiatric care unnecessarily. Assist. Prof. Dr. Hüseyin Öztoprak said at the same time children with attention deficit and hyperactivity impairment were also deprived of treatment as a result of incorrect evaluation.

Assoc. Prof. Dr. Mehmet Toycan emphasized the importance of artificial intelligence to prevent such problems and he added with the help of the intelligent technology, it is easy to distinguish brain waves and find their peculiarities with the transmission of brain waves and problems measured in children.

Toycan explained that children, who do not have attention deficit hyperactivity disorder, can be distinguished by brain waves and artificial intelligence and it can be determined if a new candidate has hyperactivity by looking at a new candidate’s brain signals.

Under the leadership of Prof. Dr. Sirel Karakaş, who is a leading name in Turkey in Clinical Psychology, Prof. Dr. Orhan Arıkan, Electrical and Electronics Engineering Department of Bilkent University, Assist. Prof. Dr. Hüseyin Öztoprak, Assoc. Prof. Dr. Mehmet Toycan, Dr. Yaşar Kemal Alp and Assoc. Prof. Dr. Elvin Doğutepe published a joint article entitled "Machine Based Learning System: Classification of Non-ADHD and Non-ADHD Participants" in Clinical Neurophysiology Magazine as part of the project that is in progress.

Last updated: 20-03-2018