AIMC Topic: Attention Deficit Disorder with Hyperactivity

Clear Filters Showing 31 to 40 of 98 articles

Identifying ADHD-Related Abnormal Functional Connectivity with a Graph Convolutional Neural Network.

Neural plasticity
Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder that is characterized by inattention, hyperactivity, and impulsivity. The neural mechanisms underlying ADHD remain inadequately understood, and current approaches...

A review of ADHD detection studies with machine learning methods using rsfMRI data.

NMR in biomedicine
Attention deficit hyperactivity disorder (ADHD) is a common mental health condition that significantly affects school-age children, causing difficulties with learning and daily functioning. Early identification is crucial, and reliable and objective ...

Detecting Autism Spectrum Disorder and Attention Deficit Hyperactivity Disorder Using Multimodal Time-Frequency Analysis with Machine Learning Using the Electroretinogram from Two Flash Strengths.

Journal of autism and developmental disorders
PURPOSE: Autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) are conditions that similarly alter cognitive functioning ability and challenge the social interaction, attention, and communication skills of affected indivi...

A systematic review on the application of machine learning models in psychometric questionnaires for the diagnosis of attention deficit hyperactivity disorder.

The European journal of neuroscience
Attention deficit hyperactivity disorder is one of the most prevalent neurodevelopmental disorders worldwide. Recent studies show that machine learning has great potential for the diagnosis of attention deficit hyperactivity disorder. The aim of the ...

Deep-Learning-Based Analysis Reveals a Social Behavior Deficit in Mice Exposed Prenatally to Nicotine.

Cells
Cigarette smoking during pregnancy is known to be associated with the incidence of attention-deficit/hyperactive disorder (ADHD). Recent developments in deep learning algorithms enable us to assess the behavioral phenotypes of animal models without c...

Classification of attention deficit hyperactivity disorder using machine learning on an EEG dataset.

Applied neuropsychology. Child
The neurodevelopmental disorder, Attention Deficit Hyperactivity Disorder (ADHD), frequently affecting youngsters, is characterized by persistent patterns of inattention, hyperactivity, and impulsivity, the etiology of which may involve a variety of ...

Predicting individual cases of major adolescent psychiatric conditions with artificial intelligence.

Translational psychiatry
Three-quarters of lifetime mental illness occurs by the age of 24, but relatively little is known about how to robustly identify youth at risk to target intervention efforts known to improve outcomes. Barriers to knowledge have included obtaining rob...

The Hybrid Deep Learning Model for Identification of Attention-Deficit/Hyperactivity Disorder Using EEG.

Clinical EEG and neuroscience
Common misbehavior among children that prevents them from paying attention to tasks and interacting with their surroundings appropriately is attention-deficit/hyperactivity disorder (ADHD). Studies of children's behavior presently face a significant ...

A robot intervention for adults with ADHD and insomnia-A mixed-method proof-of-concept study.

PloS one
OBJECTIVE: To investigate individual effects of a three-week sleep robot intervention in adults with ADHD and insomnia, and to explore participants' experiences with the intervention.