[HTML][HTML] Deep learning based on event-related EEG differentiates children with ADHD from healthy controls
Attention Deficit Hyperactivity Disorder (ADHD) is one of the most prevalent neuropsychiatric
disorders in childhood and adolescence and its diagnosis is based on clinical interviews …
disorders in childhood and adolescence and its diagnosis is based on clinical interviews …
A deep learning framework for identifying children with ADHD using an EEG-based brain network
H Chen, Y Song, X Li - Neurocomputing, 2019 - Elsevier
The convolutional neural network (CNN) is a mainstream deep learning (DL) algorithm.
However, the application of DL techniques in attention-deficit/hyperactivity disorder (ADHD) …
However, the application of DL techniques in attention-deficit/hyperactivity disorder (ADHD) …
Neurological state changes indicative of ADHD in children learned via EEG-based LSTM networks
Y Chang, C Stevenson, IC Chen… - Journal of Neural …, 2022 - iopscience.iop.org
Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that
pervasively interferes with the lives of individuals starting in childhood. Objective. To …
pervasively interferes with the lives of individuals starting in childhood. Objective. To …
[HTML][HTML] Deep learning convolutional neural networks discriminate adult ADHD from healthy individuals on the basis of event-related spectral EEG
Attention deficit hyperactivity disorder (ADHD) is a heterogeneous neurodevelopmental
disorder that affects 5% of the pediatric and adult population worldwide. The diagnosis …
disorder that affects 5% of the pediatric and adult population worldwide. The diagnosis …
Use of deep learning to detect personalized spatial-frequency abnormalities in EEGs of children with ADHD
H Chen, Y Song, X Li - Journal of neural engineering, 2019 - iopscience.iop.org
Objective. Attention-deficit/hyperactivity disorder (ADHD) is one of the most prevalent
neurobehavioral disorders. Studies have tried to find the neural correlations of ADHD with …
neurobehavioral disorders. Studies have tried to find the neural correlations of ADHD with …
Computer aided diagnosis system using deep convolutional neural networks for ADHD subtypes
Background Attention deficit hyperactivity disorder (ADHD) is a ubiquitous
neurodevelopmental disorder affecting many children. Therefore, automated diagnosis of …
neurodevelopmental disorder affecting many children. Therefore, automated diagnosis of …
Effects of spectral features of EEG signals recorded with different channels and recording statuses on ADHD classification with deep learning
M Tosun - Physical and Engineering Sciences in Medicine, 2021 - Springer
Early diagnosis of attention deficit and hyperactivity disorder (ADHD) by experts is difficult.
Some solutions using electroencephalography (EEG) signals have been presented in the …
Some solutions using electroencephalography (EEG) signals have been presented in the …
Diagnose ADHD disorder in children using convolutional neural network based on continuous mental task EEG
M Moghaddari, MZ Lighvan, S Danishvar - Computer Methods and …, 2020 - Elsevier
Abstract Background and objective Attention-Deficit/Hyperactivity Disorder (ADHD) is a
chronic behavioral disorder in children. Children with ADHD face many difficulties in …
chronic behavioral disorder in children. Children with ADHD face many difficulties in …
ADHD classification using auto-encoding neural network and binary hypothesis testing
Abstract Attention Deficit Hyperactivity Disorder (ADHD) is a highly prevalent
neurodevelopmental disease of school-age children. Early diagnosis is crucial for ADHD …
neurodevelopmental disease of school-age children. Early diagnosis is crucial for ADHD …
Applicable features of electroencephalogram for ADHD diagnosis
A Khaleghi, PM Birgani, MF Fooladi… - Research on Biomedical …, 2020 - Springer
Purpose Attention-deficit/hyperactivity disorder (ADHD) is a neuro-developmental and
psychiatric disorder, which affects 11% of children around the world. Several linear and …
psychiatric disorder, which affects 11% of children around the world. Several linear and …