AIMC Topic: Autism Spectrum Disorder

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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...

A deep learning method for autism spectrum disorder identification based on interactions of hierarchical brain networks.

Behavioural brain research
BACKGROUND: It has been recently shown that deep learning models exhibited remarkable performance of representing functional Magnetic Resonance Imaging (fMRI) data for the understanding of brain functional activities. With hierarchical structure, dee...

DeepASDPred: a CNN-LSTM-based deep learning method for Autism spectrum disorders risk RNA identification.

BMC bioinformatics
BACKGROUND: Autism spectrum disorders (ASD) are a group of neurodevelopmental disorders characterized by difficulty communicating with society and others, behavioral difficulties, and a brain that processes information differently than normal. Geneti...

Design Path for a Social Robot for Emotional Communication for Children with Autism Spectrum Disorder (ASD).

Sensors (Basel, Switzerland)
Children with autism spectrum disorder (ASD) have deficits in social interaction and expressing and understanding emotions. Based on this, robots for children with ASD have been proposed. However, few studies have been conducted about how to design a...