The relationship of early communication concerns to developmental delay and symptoms of autism spectrum disorders

2013 ◽  
Vol 16 (4) ◽  
pp. 230-236 ◽  
Author(s):  
Nicole Turygin ◽  
Johnny L. Matson ◽  
Matthew Konst ◽  
Lindsey Williams
Keyword(s):  
Autism Spectrum Disorders ◽  
Developmental Delay ◽  
Autism Spectrum ◽  
Early Communication ◽  
Spectrum Disorders ◽  
Relationship Of ◽  
The Relationship

scholarly journals Hyperacusis in Autism Spectrum Disorders

2021 ◽  
Vol 11 (4) ◽  
pp. 547-556
Author(s):  
Ali A. Danesh ◽  
Stephanie Howery ◽  
Hashir Aazh ◽  
Wafaa Kaf ◽  
Adrien A. Eshraghi
Keyword(s):  
Autism Spectrum Disorder ◽  
Autism Spectrum Disorders ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Assessment And Treatment ◽  
Spectrum Disorders ◽  
The Relationship

Hyperacusis is highly prevalent in the autism spectrum disorder (ASD) population. This auditory hypersensitivity can trigger pragmatically atypical reactions that may impact social and academic domains. Objective: The aim of this report is to describe the relationship between decreased sound tolerance disorders and the ASD population. Topics covered: The main topics discussed include (1) assessment and prevalence of hyperacusis in ASD; (2) etiology of hyperacusis in ASD; (3) treatment of hyperacusis in ASD. Conclusions: Knowledge of the assessment and treatment of decreased sound tolerance disorders within the ASD population is growing and changing.

scholarly journals Dopaminergic Gene Dosage in Autism versus Developmental Delay: From Complex Networks to Machine Learning approaches

2020 ◽  
Author(s):  
André Santos ◽  
Francisco Caramelo ◽  
Joana Barbosa de Melo ◽  
Miguel Castelo-Branco
Keyword(s):  
Machine Learning ◽  
Autism Spectrum Disorders ◽  
Network Analysis ◽  
Developmental Delay ◽  
Gene Dosage ◽  
Genetic Alterations ◽  
Autism Spectrum ◽  
Compact Set ◽  
Neural Basis ◽  
Spectrum Disorders

AbstractThe neural basis of behavioural changes in Autism Spectrum Disorders (ASD) remains a controversial issue. One factor contributing to this challenge is the phenotypic heterogeneity observed in ASD, which suggests that several different system disruptions may contribute to diverse patterns of impairment between and within study samples. Here, we took a retrospective approach, using SFARI data to study ASD by focusing on participants with genetic imbalances targeting the dopaminergic system. Using complex network analysis, we investigated the relations between participants, Gene Ontology (GO) and gene dosage related to dopaminergic neurotransmission from a polygenic point of view. We converted network analysis into a machine learning binary classification problem to differentiate ASD diagnosed participants from DD (developmental delay) diagnosed participants. Using 1846 participants to train a Random Forest algorithm, our best classifier achieved on average a diagnosis predicting accuracy of 85.18% (sd 1.11%) on a test sample of 790 participants using gene dosage features. In addition, we observed that if the classifier uses GO features it was also able to infer a correct response based on the previous examples because it is tied to a set of biological process, molecular functions and cellular components relevant to the problem. This yields a less variable and more compact set of features when comparing with gene dosage classifiers. Other facets of knowledge-based systems approaches addressing ASD through network analysis and machine learning, providing an interesting avenue of research for the future, are presented through the study.Lay SummaryThere are important issues in the differential diagnosis of Autism Spectrum Disorders. Gene dosage effects may be important in this context. In this work, we studied genetic alterations related to dopamine processes that could impact brain development and function of 2636 participants. On average, from a genetic sample we were able to correctly separate autism from developmental delay with an accuracy of 85%.

scholarly journals Society and people diagnosed with autism spectrum disorder: an analysis of message descriptors of social media

2019 ◽  
Vol 24 (4) ◽  
pp. 744-755
Author(s):  
Olga A. Vazhenina ◽  
Lidiya K. Lobodenko
Keyword(s):  
Social Media ◽  
Autism Spectrum Disorders ◽  
Digital Media ◽  
Autism Spectrum ◽  
Media Space ◽  
English Speaking ◽  
Spectrum Disorders ◽  
The Impact ◽  
The Relationship ◽  
Social Media Tool

The authors investigate the process of humanization of society in relation to people with autism spectrum disorders and its relationship with the reception of problems of this category of population by society. The authors based on the descriptors of messages in social media published in the digital media space. The article reveals the relationship between the content of messages in social media, as well as the tools of this type of media and the overall degree of humanization of society at both social and political levels. The typological features of such a social media tool as a hashtag, when covering the problems of people with autism spectrum disorders, as well as the impact of these features on the reception of messages on this topic by both domestic and English-speaking users are noted.

The Relationship Between Sleep Problems and Daytime Behavior in Children of Different Ages With Autism Spectrum Disorders

PEDIATRICS ◽  
2012 ◽  
Vol 130 (Supplement 2) ◽  
pp. S83-S90 ◽  
Author(s):  
Darryn M. Sikora ◽  
Kyle Johnson ◽  
Traci Clemons ◽  
Terry Katz
Keyword(s):  
Autism Spectrum Disorders ◽  
Sleep Problems ◽  
Autism Spectrum ◽  
Different Ages ◽  
Spectrum Disorders ◽  
The Relationship
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