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Autism Spectrum Disorder

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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...

Multiple Classification of Brain MRI Autism Spectrum Disorder by Age and Gender Using Deep Learning.

Journal of medical systems
The fact that the rapid and definitive diagnosis of autism cannot be made today and that autism cannot be treated provides an impetus to look into novel technological solutions. To contribute to the resolution of this problem through multiple classif...

Effectiveness of Robotic Intervention on Improving Social Development and Participation of Children with Autism Spectrum Disorder - A Randomised Controlled Trial.

Journal of autism and developmental disorders
Evidence-based robotic intervention programmes for children with autism spectrum disorder (ASD) have been limited. As yet, there is insufficient evidence to inform therapists, teachers, and service providers on effectiveness of robotic intervention t...

Exploring White Matter Abnormalities in Young Children with Autism Spectrum Disorder: Integrating Multi-shell Diffusion Data and Machine Learning Analysis.

Academic radiology
RATIONALE AND OBJECTIVES: This study employed tract-based spatial statistics (TBSS) to investigate abnormalities in the white matter microstructure among children with autism spectrum disorder (ASD). Additionally, an eXtreme Gradient Boosting (XGBoos...

Seeing through a robot's eyes: A cross-sectional exploratory study in developing a robotic screening technology for autism.

Autism research : official journal of the International Society for Autism Research
The present exploratory cross-sectional case-control study sought to develop a reliable and scalable screening tool for autism using a social robot. The robot HUMANE, installed with computer vision and linked with recognition technology, detected the...

Modified Meta Heuristic BAT with ML Classifiers for Detection of Autism Spectrum Disorder.

Biomolecules
ASD (autism spectrum disorder) is a complex developmental and neurological disorder that impacts the social life of the affected person by disturbing their capability for interaction and communication. As it is a behavioural disorder, early treatment...

Bimodal Feature Analysis with Deep Learning for Autism Spectrum Disorder Detection.

International journal of neural systems
Autism Spectrum Disorder (ASD) is a complex and heterogeneous neurodevelopmental disorder which affects a significant proportion of the population, with estimates suggesting that about 1 in 100 children worldwide are affected by ASD. This study intro...

A Scoping Review of the Use of Robotics Technologies for Supporting Social-Emotional Learning in Children with Autism.

Journal of autism and developmental disorders
This scoping review synthesises the current research into robotics technologies for promoting social-emotional learning in children with autism spectrum disorder. It examines the types of robotics technologies employed, their applications, and the ga...

On effectively predicting autism spectrum disorder therapy using an ensemble of classifiers.

Scientific reports
An ensemble of classifiers combines several single classifiers to deliver a final prediction or classification decision. An increasingly provoking question is whether such an ensemble can outperform the single best classifier. If so, what form of ens...

Machine Learning Differentiation of Autism Spectrum Sub-Classifications.

Journal of autism and developmental disorders
PURPOSE: Disorders on the autism spectrum have characteristics that can manifest as difficulties with communication, executive functioning, daily living, and more. These challenges can be mitigated with early identification. However, diagnostic crite...