AIMC Topic: Autism Spectrum Disorder

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EEG-Based Computer Aided Diagnosis of Autism Spectrum Disorder Using Wavelet, Entropy, and ANN.

BioMed research international
Autism spectrum disorder (ASD) is a type of neurodevelopmental disorder with core impairments in the social relationships, communication, imagination, or flexibility of thought and restricted repertoire of activity and interest. In this work, a new c...

Screening of autism based on task-free fMRI using graph theoretical approach.

Psychiatry research. Neuroimaging
Studies on autism spectrum disorder (ASD) have indicated several dysfunctions in the structure, and functional organization of the brain. However, findings have not been established as a general diagnostic tool yet. In this regard, current study prop...

Improving therapeutic outcomes in autism spectrum disorders: Enhancing social communication and sensory processing through the use of interactive robots.

Journal of psychiatric research
For children with autism spectrum disorders (ASDs), social robots are increasingly utilized as therapeutic tools in order to enhance social skills and communication. Robots have been shown to generate a number of social and behavioral benefits in chi...

Development of a Machine Learning Algorithm for the Surveillance of Autism Spectrum Disorder.

PloS one
The Autism and Developmental Disabilities Monitoring (ADDM) Network conducts population-based surveillance of autism spectrum disorder (ASD) among 8-year old children in multiple US sites. To classify ASD, trained clinicians review developmental eval...

Combining natural language processing and network analysis to examine how advocacy organizations stimulate conversation on social media.

Proceedings of the National Academy of Sciences of the United States of America
Social media sites are rapidly becoming one of the most important forums for public deliberation about advocacy issues. However, social scientists have not explained why some advocacy organizations produce social media messages that inspire far-rangi...

Predicting symptom severity in autism spectrum disorder based on cortical thickness measures in agglomerative data.

NeuroImage
Machine learning approaches have been widely used for the identification of neuropathology from neuroimaging data. However, these approaches require large samples and suffer from the challenges associated with multi-site, multi-protocol data. We prop...

Support vector machine model of developmental brain gene expression data for prioritization of Autism risk gene candidates.

Bioinformatics (Oxford, England)
MOTIVATION: Autism spectrum disorders (ASD) are a group of neurodevelopmental disorders with clinical heterogeneity and a substantial polygenic component. High-throughput methods for ASD risk gene identification produce numerous candidate genes that ...

Atypical Asymmetry for Processing Human and Robot Faces in Autism Revealed by fNIRS.

PloS one
Deficits in the visual processing of faces in autism spectrum disorder (ASD) individuals may be due to atypical brain organization and function. Studies assessing asymmetric brain function in ASD individuals have suggested that facial processing, whi...

Use of machine learning to improve autism screening and diagnostic instruments: effectiveness, efficiency, and multi-instrument fusion.

Journal of child psychology and psychiatry, and allied disciplines
BACKGROUND: Machine learning (ML) provides novel opportunities for human behavior research and clinical translation, yet its application can have noted pitfalls (Bone et al., 2015). In this work, we fastidiously utilize ML to derive autism spectrum d...

Identifying children with autism spectrum disorder based on their face processing abnormality: A machine learning framework.

Autism research : official journal of the International Society for Autism Research
The atypical face scanning patterns in individuals with Autism Spectrum Disorder (ASD) has been repeatedly discovered by previous research. The present study examined whether their face scanning patterns could be potentially useful to identify childr...