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Autism Spectrum Disorder

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Artificial neural network for evaluating sleep spindles and slow waves after transcranial magnetic stimulation in a child with autism.

Neurocase
Sleep spindles (SS) and slow waves (SW) serve as indicators of the integrity of thalamocortical connections, which are often compromised in individuals with autism spectrum disorder (ASD). Transcranial magnetic stimulation (TMS) can modulate brain ac...

Exploring sensory alterations and repetitive behaviors in children with autism spectrum disorder from the perspective of artificial neural networks.

Research in developmental disabilities
BACKGROUND: Restrictive repetitive behaviors (RRBs) and sensory processing disorders are core symptoms of autism spectrum disorder (ASD). Their relationship is reported, but existing data are conflicting as to whether they are related but distinct, o...

Early diagnostic value of home video-based machine learning in autism spectrum disorder: a meta-analysis.

European journal of pediatrics
UNLABELLED: Machine learning (ML) based on remote video has shown ideal diagnostic value in autism spectrum disorder (ASD). Here, we conducted a meta-analysis of the diagnostic value of home video-based ML in ASD. Relevant articles were systematicall...

Wearable EEG Neurofeedback Based-on Machine Learning Algorithms for Children with Autism: A Randomized, Placebo-controlled Study.

Current medical science
OBJECTIVE: Behavioral interventions have been shown to ameliorate the electroencephalogram (EEG) dynamics underlying the behavioral symptoms of autism spectrum disorder (ASD), while studies have also demonstrated that mirror neuron mu rhythm-based EE...

Recognition of autism in subcortical brain volumetric images using autoencoding-based region selection method and Siamese Convolutional Neural Network.

International journal of medical informatics
BACKGROUND: Autism Spectrum Disorder (ASD) is a neurodevelopmental condition that affects social interactions and behavior. Accurate and early diagnosis of ASD is still challenging even with the improvements in neuroimaging technology and machine lea...

Predicting neurodevelopmental disorders using machine learning models and electronic health records - status of the field.

Journal of neurodevelopmental disorders
Machine learning (ML) is increasingly used to identify patterns that could predict neurodevelopmental disorders (NDDs), such as autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD). One key source of multilevel data for ...

A deep learning model of dorsal and ventral visual streams for DVSD.

Scientific reports
Artificial intelligence (AI) methods attempt to simulate the behavior and the neural activity of the brain. In particular, Convolutional Neural Networks (CNNs) offer state-of-the-art models of the ventral visual stream. Furthermore, no proposed model...

Pilot study protocol evaluating the impact of telerobotics interactions with autistic children during a Denver intervention on communication skills using single-case experimental design.

BMJ open
INTRODUCTION: For several years, studies have been conducted on the contribution of social robots as an intervention tool for children with autism spectrum disorder (ASD). One of the early intervention models recommended by the French National Author...

Identification of autism spectrum disorder using electroencephalography and machine learning: a review.

Journal of neural engineering
Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by communication barriers, societal disengagement, and monotonous actions. Traditional diagnostic methods for ASD rely on clinical observations and behavioural assessments...

Screening biomarkers for autism spectrum disorder using plasma proteomics combined with machine learning methods.

Clinica chimica acta; international journal of clinical chemistry
BACKGROUND AND AIMS: Autism spectrum disorder (ASD) is a common neurodevelopmental disorder in children. Early intervention is effective. Investigation of novel blood biomarkers of ASD facilitates early detection and intervention.