AIMC Topic: Autism Spectrum Disorder

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Evaluation of interpretability for deep learning algorithms in EEG emotion recognition: A case study in autism.

Artificial intelligence in medicine
Current models on Explainable Artificial Intelligence (XAI) have shown a lack of reliability when evaluating feature-relevance for deep neural biomarker classifiers. The inclusion of reliable saliency-maps for obtaining trustworthy and interpretable ...

Development and Validation of a Joint Attention-Based Deep Learning System for Detection and Symptom Severity Assessment of Autism Spectrum Disorder.

JAMA network open
IMPORTANCE: Joint attention, composed of complex behaviors, is an early-emerging social function that is deficient in children with autism spectrum disorder (ASD). Currently, no methods are available for objectively quantifying joint attention.

Artificial scaffolding: Augmenting social cognition by means of robot technology.

Autism research : official journal of the International Society for Autism Research
The concept of scaffolding refers to the support that the environment provides in the acquisition and consolidation of new abilities. Technological advancements allow for support in the acquisition of cognitive capabilities, such as second language a...

Computer-aided diagnosis of autism spectrum disorder from EEG signals using deep learning with FAWT and multiscale permutation entropy features.

Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine
Autism spectrum disorder (ASD), a neurodevelopment disorder, is characterized by significant difficulties in social interaction and emerges as a major threat to children. Its computer-aided diagnosis used by neurologists improves the detection proces...

Abnormal amygdala functional connectivity and deep learning classification in multifrequency bands in autism spectrum disorder: A multisite functional magnetic resonance imaging study.

Human brain mapping
Previous studies have explored resting-state functional connectivity (rs-FC) of the amygdala in patients with autism spectrum disorder (ASD). However, it remains unclear whether there are frequency-specific FC alterations of the amygdala in ASD and w...

Effectiveness of a Robot-Assisted Psychological Intervention for Children with Autism Spectrum Disorder.

Journal of autism and developmental disorders
Difficulties with social interaction characterise children with Autism Spectrum Disorders and have a negative impact in their everyday life. Integrating a social-humanoid robot within the standard clinical treatment has been proven promising. The mai...

Intervention with a humanoid robot avatar for individuals with social anxiety disorders comorbid with autism spectrum disorders.

Asian journal of psychiatry
For some individuals with social anxiety disorders (SAD) comorbid with autism spectrum disorders (ASD), it is difficult to speak in front of others. Herein, we report the case of a patient with SAD comorbid with ASD who could not speak in front of ot...

Identifying autism spectrum disorder in resting-state fNIRS signals based on multiscale entropy and a two-branch deep learning network.

Journal of neuroscience methods
BACKGROUND: The demand for early and precise identification of autism spectrum disorder (ASD) presented a challenge to the prediction of ASD with a non-invasive neuroimaging method.

Young children with autism show atypical prefrontal cortical responses to humanoid robots: An fNIRS study.

International journal of psychophysiology : official journal of the International Organization of Psychophysiology
BACKGROUND: Previous behavioral studies have found that children with autism spectrum disorder (ASD) show greater interest in humanoid robots than in humans. However, the neural mechanism underlying this is not clear. This study compared brain activa...