A review of deep learning methods in the diagnosis of attention deficit hyperactivity disorder

Subject Areas : Information Technology in Engineering Design (ITED) Journal

Akram Feizi ¹ , Seyyed Abeh Hosseini ² , محبوبه هوشمند ³

1 - Department of Computer Engineering., Mashhad Branch, Islamic Azad University, Mashhad, Iran
2 - 3Department of Electrical Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran
3 - گروه کامپیوتر، دانشگاه آزاد اسلامی واحد مشهد، استادیار

Received: 2024-08-03 Accepted : 2024-10-01 Published : 2024-09-25

Keywords: Attention deficit/hyperactivity disorder, brain signals, magnetic resonance images, deep learning.,

Abstract :

Attention deficit/hyperactivity disorder (ADHD) is one of the most common behavioral disorders in children and adolescents. Accurate and timely diagnosis is important to start appropriate treatment. In recent years, with the progress in the fields of machine learning and deep learning, researchers have paid special attention to better diagnosis of ADHD. This research examines the applications of deep learning in the diagnosis of ADHD through the analysis of various data such as electroencephalography signals and magnetic resonance images. It also examines the challenges and limitations in this field. The aim of this research is to provide a comprehensive perspective on the potential of using deep learning in the diagnosis of ADHD and the future directions of research in this field. It is hoped that this research can pave the way for researchers in this field as an efficient guide.

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