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Autism Spectrum Disorder

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Topology-guided cyclic brain connectivity generation using geometric deep learning.

Journal of neuroscience methods
BACKGROUND: There is a growing need for analyzing medical data such as brain connectomes. However, the unavailability of large-scale training samples increases risks of model over-fitting. Recently, deep learning (DL) architectures quickly gained mom...

Single Volume Image Generator and Deep Learning-Based ASD Classification.

IEEE journal of biomedical and health informatics
Autism spectrum disorder (ASD) is an intricate neuropsychiatric brain disorder characterized by social deficits and repetitive behaviors. Deep learning approaches have been applied in clinical or behavioral identification of ASD; most erstwhile model...

Automated identification of postural control for children with autism spectrum disorder using a machine learning approach.

Journal of biomechanics
It is unclear whether postural sway characteristics could be used as diagnostic biomarkers for autism spectrum disorder (ASD). The purpose of this study was to develop and validate an automated identification of postural control patterns in children ...

Population Graph-Based Multi-Model Ensemble Method for Diagnosing Autism Spectrum Disorder.

Sensors (Basel, Switzerland)
With the advancement of brain imaging techniques and a variety of machine learning methods, significant progress has been made in brain disorder diagnosis, in particular Autism Spectrum Disorder. The development of machine learning models that can di...

Predicting brain age with complex networks: From adolescence to adulthood.

NeuroImage
In recent years, several studies have demonstrated that machine learning and deep learning systems can be very useful to accurately predict brain age. In this work, we propose a novel approach based on complex networks using 1016 T1-weighted MRI brai...

Ordered interpersonal synchronisation in ASD children via robots.

Scientific reports
Children with autistic spectrum disorders (ASD) experience persistent disrupted coordination in interpersonal synchronisation that is thought to be associated with deficits in neural connectivity. Robotic interventions have been explored for use with...

The study of the differences between low-functioning autistic children and typically developing children in the processing of the own-race and other-race faces by the machine learning approach.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
OBJECTIVE: Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder which affects the developmental trajectory in several behavioral domains, including impairments of social communication and stereotyped behavior. Unlike typicall...

Optimal robot for intervention for individuals with autism spectrum disorders.

Psychiatry and clinical neurosciences
With recent rapid advances in technology, human-like robots have begun functioning in a variety of ways. As increasing anecdotal evidence suggests, robots may offer many unique opportunities for helping individuals with autism spectrum disorders (ASD...

The DREAM Dataset: Supporting a data-driven study of autism spectrum disorder and robot enhanced therapy.

PloS one
We present a dataset of behavioral data recorded from 61 children diagnosed with Autism Spectrum Disorder (ASD). The data was collected during a large-scale evaluation of Robot Enhanced Therapy (RET). The dataset covers over 3000 therapy sessions and...

Self-initiations in young children with autism during Pivotal Response Treatment with and without robot assistance.

Autism : the international journal of research and practice
The initiation of social interaction is often defined as a core deficit of autism spectrum disorder. Optimizing these self-initiations is therefore a key component of Pivotal Response Treatment, an established intervention for children with autism sp...