Deep learning methods have been widely applied in Attention Deficit Hyperactivity Disorder
(ADHD) classification in the past decade due to their effective learned features. However …

The attention-deficit hyperactivity disorder also known as ADHD is a collective mental health
syndrome in young groups. Efficacious involuntary analysis of ADHD which is based on …

A mixed literature implicates atypical connectivity involving attentional, reward and task
inhibition networks in ADHD. The neural mechanisms underlying the utility of behavioral …

ADHD is a neurodevelopmental disorder that affects children. ADHD can often persist in
adulthood too. Children diagnosed with ADHD have significantly increased across the globe …

Attention-deficit hyperactivity disorder (ADHD) is a persistent condition with repeated issues,
such as difficulty maintaining attention, impetuous behavior, and hyperactivity. It severely …

Increasing attention has been paid to attention-deficit hyperactivity disorder (ADHD)-
assisted diagnosis using functional brain networks (FBNs) since FBNs-based ADHD …

Abstract Background: Attention Deficit Hyperactivity Disorder (ADHD) is one of the most
common neurodevelopmental disorders during childhood, however the diagnosis procedure …

We sought to revolutionize the classification of Attention-Deficit/Hyperactivity Disorder
(ADHD) by pioneering an innovative approach that seamlessly integrated auditory and …

Abstract Attention Deficit Hyperactivity Disorder (ADHD) is a mental disorder that is marked
by abnormally high levels of impulsivity, hyperactivity and inattention. One of the methods to …

Attention deficit hyperactivity disorder (ADHD) can have a negative impact on children's
development, even into adulthood, so the early diagnosis and screening for ADHD can be …