AIMC Topic: Autistic Disorder

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Can artificial intelligence and face recognition using deep learning detect emotions in children with autism?

PloS one
BACKGROUND/OBJECTIVES: This study aimed to evaluate the performance of deep learning models for recognizing facial expressions of children with autism through face recognition technologies.

New intelligent music therapy method for applications of enhancing social skills of autism children based on TL-GCN and deep learning.

Scientific reports
To address the long-standing challenges children with autism face in social skills and emotional regulation, this study introduces Emotion-based Music Intelligent Network (EmoMusik-Net)-a deep learning model designed for intelligent music therapy. Th...

A joint complex network and machine learning approach for the identification of discriminative gene communities in autistic brain.

PloS one
Autism is a genetically and clinically very heterogeneous group of disorders. Gene co-expression network analysis can help unravel its complex genetic architecture through the identification of communities of genes that are dysregulated. Using a publ...

Predictive modeling of adaptive behavior trajectories in autism: insights from a clinical cohort study.

Translational psychiatry
Research aimed at understanding how baseline clinical and demographic characteristics influence outcomes over time is critically important to inform individualized therapeutic programs for children with neurodevelopmental differences. This study char...

Overcoming Site Variability in Multisite fMRI Studies: an Autoencoder Framework for Enhanced Generalizability of Machine Learning Models.

Neuroinformatics
Harmonizing multisite functional magnetic resonance imaging (fMRI) data is crucial for eliminating site-specific variability that hinders the generalizability of machine learning models. Traditional harmonization techniques, such as ComBat, depend on...

Temporal dynamics of early child-clinician prosodic synchrony predict one year autism intervention outcomes using AI driven affective computing.

Scientific reports
The patient-therapist interpersonal dynamics is a cornerstone of psychotherapy, yet how it shapes clinical outcomes remains underexplored and difficult to quantify. This is also true in autism, where interpersonal interplay is recognized as an active...

Use of computer vision analysis for labeling inattention periods in EEG recordings with visual stimuli.

Scientific reports
Electroencephalography (EEG) recordings with visual stimuli require detailed coding to determine the periods of participant's attention. Here we propose to use a supervised machine learning model and off-the-shelf video cameras only. We extract compu...

A deep learning model for diagnosing autism using brain time series.

Neuroscience
The early identification of autism is especially critical as it can significantly enhance the effectiveness of intervention strategies. However, the recognition task remains challenging due to the subtle differences between ASD patients and neurotypi...

Enhancing theory of mind in autism through humanoid robot interaction in a randomized controlled trial.

Scientific reports
Autism Spectrum Disorder presents significant challenges in social cognition, particularly in understanding others' thoughts, emotions, and intentions. Traditional interventions often rely on role-playing games with human therapists or inanimate obje...

Predicting autism from written narratives using deep neural networks.

Scientific reports
Despite the heterogeneity of language and communication abilities within the autistic population, challenges associated with the pragmatic (social) use of speech remain consistently observable across the entire spectrum of autism. Therefore, the stud...