Now showing items 1-2 of 2

  • Classification of ADHD Using Ensemble Algorithms with Deep Learning and Hand Crafted Features 

    Authors:Çiçek, Gülay; Çevik, Mesut; Akan, Aydın
    Publisher and Date:(IEEE, 2019)
    Attention Deficit Hyperactivity (ADHD) is a common neurodevelopmental disorder that typically appears in early childhood. Methods developed for diagnosing gives different results at different times. This is a major obstacle in the diagnosis of disease. Diagnosis model of ADHD must be unique, objective, and reliable. In this study, comparative evaluations of both manual and deep features for classification of structural magnetic resonance images is presented. For this purpose, datasets of NPIstanbul ...

  • The Effect of Data Augmentation on ADHD Diagnostic Model using Deep Learning 

    Authors:Çiçek, Gülay; Özmen, Atilla; Akan, Aydin
    Publisher and Date:(IEEE, 2019)
    Attention Deficit Hyperactivity Disorder (ADHD) is a neuro-behavioral hyperactivity disorder. It is frequently seen in childhood and youth, and lasts a lifetime unless treated.The ADHD classification model should be objective and robust. Correct diagnosis usually depends on the knowledge and experience of health professionals. In this respect, an automated method to be developed for the ADHD classification model is of great importance for clinicians. In this study, the effect of data augmentation ...