AIMC Topic: Autism Spectrum Disorder

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Uncovering Brain Differences in Preschoolers and Young Adolescents with Autism Spectrum Disorder Using Deep Learning.

International journal of neural systems
Identifying brain abnormalities in autism spectrum disorder (ASD) is critical for early diagnosis and intervention. To explore brain differences in ASD and typical development (TD) individuals by detecting structural features using T1-weighted magnet...

Social robots in the instruction of social skills in autism: a comprehensive descriptive analysis of single-case experimental designs.

Disability and rehabilitation. Assistive technology
PURPOSE: The rapid technological advances, the traits of individuals with ASD and their interest in technology are promising for the instruction of social skills to individuals with autism spectrum disorder (ASD) using various technological intervent...

Contrastive machine learning reveals the structure of neuroanatomical variation within autism.

Science (New York, N.Y.)
Autism spectrum disorder (ASD) is highly heterogeneous. Identifying systematic individual differences in neuroanatomy could inform diagnosis and personalized interventions. The challenge is that these differences are entangled with variation because ...

Development of a phenotype ontology for autism spectrum disorder by natural language processing on electronic health records.

Journal of neurodevelopmental disorders
BACKGROUND: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by restricted, repetitive behavior, and impaired social communication and interactions. However, significant challenges remain in diagnosing and subtyp...

Identifying Visual Attention Features Accurately Discerning Between Autism and Typically Developing: a Deep Learning Framework.

Interdisciplinary sciences, computational life sciences
Atypical visual attention is a hallmark of autism spectrum disorder (ASD). Identifying the attention features accurately discerning between people with ASD and typically developing (TD) at the individual level remains a challenge. In this study, we d...

Facial Features Detection System To Identify Children With Autism Spectrum Disorder: Deep Learning Models.

Computational and mathematical methods in medicine
Autism spectrum disorder (ASD) is a neurodevelopmental disorder associated with brain development that subsequently affects the physical appearance of the face. Autistic children have different patterns of facial features, which set them distinctivel...

Classification and Detection of Autism Spectrum Disorder Based on Deep Learning Algorithms.

Computational intelligence and neuroscience
Autism spectrum disorder (ASD) is a type of mental illness that can be detected by using social media data and biomedical images. Autism spectrum disorder (ASD) is a neurological disease correlated with brain growth that later impacts the physical im...

Reproducible neuroimaging features for diagnosis of autism spectrum disorder with machine learning.

Scientific reports
Autism spectrum disorder (ASD) is the fourth most common neurodevelopmental disorder, with a prevalence of 1 in 160 children. Accurate diagnosis relies on experts, but such individuals are scarce. This has led to increasing interest in the developmen...

Effects of Parental Involvement in Robot-Assisted Autism Therapy.

Journal of autism and developmental disorders
Parental involvement in traditional autism therapy is key to the effective treatment of children with ASD. Little is known about parental involvement in robot-assisted autism therapy (RAAT)-novel therapeutic support for children with ASD. Our study i...

A Systematic Review of Research on Robot-Assisted Therapy for Children with Autism.

Sensors (Basel, Switzerland)
Recent studies have shown that children with autism may be interested in playing with an interactive robot. Moreover, the robot can engage these children in ways that demonstrate essential aspects of human interaction, guiding them in therapeutic ses...