A Detailed Examination of Deep Learning Models for Detection of Attention Deficit Hyperactivity Disorder(ADHD)

the neurodevelopmental disorder ADHD (Attention Deficit Hyperactivity Disorder) has an impact on a person's brain function and it is also highly heritable. It affects many people's daily life and they are unaware that they are affected. Evidence from twin and family research indicates shared genetic predisposition between ADHD, even if their underlying etiologies have not yet been fully explained. The use of data augmentation (DA), which can result in a quicker convergence to solution and improved prediction accuracy, is crucial to the success of CNN models. By using ADHD-200 Dataset and Different types of classification techniques, feature selection modules and fMRI images as input for early detection of ADHD.