scholarly journals Applying Artificial Intelligence for Diagnostic Classification of Korean Autism Spectrum Disorder

2020 ◽  
Vol 17 (11) ◽  
pp. 1090-1095
Author(s):  
Eun Soo Choi ◽  
Hee Jeong Yoo ◽  
Min Soo Kang ◽  
Soon Ae Kim
Keyword(s):  
Artificial Intelligence ◽  
Autism Spectrum Disorder ◽  
Diagnostic Algorithm ◽  
Autism Spectrum ◽  
Diagnostic Interview ◽  
Primary Objective ◽  
Spectrum Disorder ◽  
Verbal Language ◽  
Text Revision ◽  
Set Up

Objective The primary objective of this study was to predict subgroups of autism spectrum disorder (ASD) based on the Diagnostic Statistical Manual for Mental Disorders-IV Text Revision (DSM-IV-TR) by machine learning (ML). The secondary objective was to set up a ranking of Autism Diagnostic Interview-Revised (ADI-R) diagnostic algorithm items based on ML, and to confirm whether ML can sufficiently predict the diagnosis with these minimum items.Methods In the first experiment, a multiclass decision forest algorithm was applied, and the diagnostic algorithm score value of 1,269 Korean ADI-R test data was used for prediction. In the second experiment, we used 539 Korean ADI-R case data (over 48 months with verbal language) to apply mutual information to rank items used in the ADI diagnostic algorithm.Results In the first experiment, the results of predicting in the case of pervasive developmental disorder not otherwise specified as “ASD” were almost three times higher than predicting it as “No diagnosis.” In the second experiment, the top 10 ranking items of ADI-R were mainly related to the quality abnormality of communication.Conclusion In conclusion, we verified the applicability of ML in diagnosis and found that the application of artificial intelligence for rapid diagnosis or screening of ASD patients may be useful.

scholarly journals Adapting and validating the Autism Diagnostic Interview - Revised for use with deaf children and young people

Autism ◽  
2021 ◽  
pp. 136236132110291
Author(s):  
Barry Wright ◽  
Helen Phillips ◽  
Victoria Allgar ◽  
Jennifer Sweetman ◽  
Rachel Hodkinson ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Expert Panel ◽  
Diagnostic Algorithm ◽  
Children With Autism ◽  
Autism Spectrum ◽  
Diagnostic Interview ◽  
Spectrum Disorder ◽  
Deaf Children ◽  
Clinical Assessments ◽  
Autism Diagnostic Interview

A Delphi consensus methodology was used to adapt the Autism Diagnostic Interview–Revised for the assessment of deaf children with suspected autism spectrum disorder. Each Autism Diagnostic Interview–Revised item was considered by a panel of nine international experts in terms of relevance and acceptability. Modifications were proposed and agreed by the expert panel for 45% of items. The pre-specified criterion for agreement between experts was set at 80% for each item. A first validation of the revised version, adapted for deaf children (Autism Diagnostic Interview–Revised Deaf Adaptation), was undertaken with a UK sample of 78 parents/carers of deaf children with autism spectrum disorder and 126 parents/carers with deaf children without autism spectrum disorder. When compared to National Institute for Health and Care Excellence guideline standard clinical assessments, the Autism Diagnostic Interview–Revised Deaf Adaptation diagnostic algorithm cut-off/threshold scores achieved a sensitivity of 89% (79%–96%) and specificity of 81% (70%–89%) for autism spectrum disorder. The alpha coefficients for each algorithm symptom domain ranged from 0.80 to 0.91, suggesting that the items had high internal consistency. Our findings indicate that the Autism Diagnostic Interview–Revised Deaf Adaptation is likely to be a useful measure for the assessment of deaf children with suspected autism spectrum disorder, although further research is needed. Lay abstract Autism assessment processes need to improve for deaf children as they are currently being diagnosed later than their hearing counterparts and misdiagnosis can occur. We took one of the most commonly used parent developmental interviews for autism spectrum disorder the Autism Diagnostic Interview–Revised and adapted it using international expert advice. Modifications were proposed and agreed by the expert panel for 45% of items; the remaining 55% of items were unchanged. We then tested the revised version, adapted for deaf children (Autism Diagnostic Interview–Revised Deaf Adaptation), in a UK sample of 78 parents/carers of deaf children with autism spectrum disorder and 126 parents/carers with deaf children without autism spectrum disorder. When compared to National Institute for Health and Care Excellence guideline standard clinical assessments, the Autism Diagnostic Interview–Revised Deaf Adaptation diagnostic algorithm threshold scores could identify those deaf children with a definite diagnosis (true autism spectrum disorder positives) well (sensitivity of 89% (79%–96%)) and those deaf children who did not have autism spectrum disorder (true autism spectrum disorder negatives) well (specificity of 81% (70%–89%)). Our findings indicate that the Autism Diagnostic Interview–Revised Deaf Adaptation is likely to prove a useful measure for the assessment of deaf children with suspected autism spectrum disorder and that further research would be helpful.

Co-occurring trajectories of anxiety and insistence on sameness behaviour in autism spectrum disorder

2020 ◽  
Vol 218 (1) ◽  
pp. 20-27
Author(s):  
Danielle A. Baribeau ◽  
Simone Vigod ◽  
Eleanor Pullenayegum ◽  
Connor M. Kerns ◽  
Pat Mirenda ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Middle Childhood ◽  
Child Behavior Checklist ◽  
Childhood Anxiety ◽  
Parent Report ◽  
Autism Spectrum ◽  
Diagnostic Interview ◽  
Anxiety Symptoms ◽  
Spectrum Disorder ◽  
Insistence On Sameness

BackgroundChildren with autism spectrum disorder (ASD) have increased susceptibility to anxiety disorders. Variation in a common ASD symptom, insistence on sameness behaviour, may predict future anxiety symptoms.AimsTo describe the joint heterogeneous longitudinal trajectories of insistence on sameness and anxiety in children with ASD and to characterise subgroups at higher risk for anxiety.MethodIn a longitudinal ASD cohort (n = 421), insistence on sameness behaviour was measured using the Autism Diagnostic Interview-Revised at approximately ages 3, 6 and 11 years. Anxiety was quantified at 8 time points between ages 3 and 11 years using the Child Behavior Checklist (CBCL) (parent report). Clusters of participants following similar trajectories were identified using group-based and joint trajectory modelling.ResultsThree insistence on sameness trajectories were identified: (a) ‘low-stable’ (41.7% of participants), (b) ‘moderate-increasing’ (52.0%) and (c) ‘high-peaking’ (i.e. increasing then stabilising/decreasing behaviour) (6.3%). Four anxiety trajectories were identified: (a) ‘low-increasing’ (51.0%), (b) ‘moderate-decreasing’ (16.2%), (c) ‘moderate-increasing’ (19.6%) and (d) ‘high-stable’ (13.1%). Of those assigned to the ‘high-peaking’ insistence on sameness trajectory, 95% jointly followed an anxiety trajectory that surpassed the threshold for clinical concern (T-score >65) by middle childhood (anxiety trajectories 3 or 4). Insistence on sameness and anxiety trajectories were similar in severity and direction for 64% of the sample; for 36%, incongruous patterns were seen (e.g. decreasing anxiety and increasing insistence on sameness).ConclusionsThe concurrent assessment of insistence on sameness behaviour and anxiety in ASD may help in understanding current symptom profiles and anticipating future trajectories. High preschool insistence on sameness in particular may be associated with elevated current or future anxiety symptoms.

scholarly journals An ontology for Autism Spectrum Disorder (ASD) to infer ASD phenotypes from Autism Diagnostic Interview-Revised data

2015 ◽  
Vol 56 ◽  
pp. 333-347 ◽  
Author(s):  
Omri Mugzach ◽  
Mor Peleg ◽  
Steven C. Bagley ◽  
Stephen J. Guter ◽  
Edwin H. Cook ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Autism Spectrum ◽  
Diagnostic Interview ◽  
Spectrum Disorder ◽  
Autism Diagnostic Interview

scholarly journals Autism Spectrum Disorder Therapy: Analysis of Artificial Intelligence integrated Robotic Approach

2022 ◽  
Vol 2161 (1) ◽  
pp. 012038
Author(s):  
Ananya Ananth Rao ◽  
Shaun Qien Yeau Tan ◽  
R Raghavi ◽  
Archit Srivastava ◽  
C H Renumadhavi
Keyword(s):  
Artificial Intelligence ◽  
Autism Spectrum Disorder ◽  
Social Interaction ◽  
Autism Spectrum ◽  
Research Field ◽  
Spectrum Disorder ◽  
Treatment Protocols ◽  
Behavioural Analysis ◽  
Technological Methods ◽  
Viable Method

Abstract Autism Spectrum Disorder is a developmental disorder that may manifest in a myriad of ways such as difficulties in social interaction and a tendency to engage in repetitive patterns of behaviour. Over the years, several kinds of treatment protocols have been proposed and implemented. One such area that is attracting the attention of researchers in the field is a robot-based approach in the treatment of children diagnosed with the disorder. Here we propose a viable method via the integration of apex technological methods like Artificial Intelligence, Machine Learning and Medical Robotics, coupling it with problem specific algorithms in OpenCV along with principles of Applied Behavioural Analysis to help possibly alleviate a key symptom displayed by children in terms of level of social interaction - that of eye-contact. This would be achieved via an AI-integrated Robotic Framework. The project also considers the possibility of inclusion of the growing research field of Quantum Computing to realize the process and investigates its viability as a potential source of innovation in the future.

scholarly journals Erythrocyte Deformability in Children With Autism Spectrum Disorder: Correlation With Clinical Features

2019 ◽  
pp. S307-S313
Author(s):  
T. JASENOVEC ◽  
D. RADOSINSKA ◽  
H. CELUSAKOVA ◽  
D. FILCIKOVA ◽  
K. BABINSKA ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Clinical Symptoms ◽  
Intrinsic Property ◽  
Tissue Perfusion ◽  
Significant Negative Correlation ◽  
Biomechanical Properties ◽  
Autism Spectrum ◽  
Diagnostic Interview ◽  
Erythrocyte Deformability ◽  
Spectrum Disorder

Biomechanical properties of erythrocytes play an important role in health and disease. Deformability represents intrinsic property of erythrocytes to undergo deformation that is crucial for their passage through the narrow capillaries. The erythrocyte damage can lead to compromised tissue perfusion and consequently play a role in the pathogenesis of various diseases including neurological ones. Data available in databases indicate that erythrocytes in autism spectrum disorder (ASD) are altered. This may affect the clinical symptoms of ASD. The aim of our study was to determine erythrocyte deformability in 54 children with ASD and correlate it with clinical symptoms. We found significant negative correlation between erythrocyte deformability and score in C domain of the Autism Diagnostic Interview-Revised (ADI-R) diagnostic tool describing the measure of restrictive, repetitive, and stereotyped behaviors and interests, mainly observable in C1 and C2, but not in C3 and C4 subdomains. This supports the findings of other authors and suggest that behavioral domain C comprises of more subcategories with different underlying etiology. Our results also indicate that abnormalities in erythrocyte deformability may be involved in ASD pathomecha-nisms and contribute to its clinical manifestation. Further research is necessary to bring more data and identify erythrocyte deformability as prognostic biomarker in ASD.

The Educational System and Autism Spectrum Disorder

2018 ◽  
Author(s):  
Michael Ellis
Keyword(s):  
Autism Spectrum Disorder ◽  
School District ◽  
Educational System ◽  
School System ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Special Education Teacher ◽  
Iep Meeting ◽  
Caring Teachers ◽  
Set Up

Navigating the educational system is likely the most treacherous and frustrating part of raising a child with autism spectrum disorder (ASD). Often parents feel that they have to be lawyers to understand the rights of their child and to advocate for appropriate resources at school. I know firsthand how difficult this can be. I can honestly state that next to a child’s severe tantrums, this is the most frustrating and pervasive problem parents may encounter. Typically, year after year and IEP (individualized education program) meeting after IEP meeting, the battle for even substandard education and services continues. Parents naturally assume that the school system would have to maintain certain standards and provide appropriate education and therapies for their child. One might even believe that the special education teacher, and the school district itself, would be more expert than the parent. Unfortunately, this is rarely the case. Training, especially specific to ASD, is usually quite poor. Aside from some very caring teachers, the system is often set up to fail the child. The school district likely saves money by refusing to provide additional services, modifications, or accommodations for your child. Typically, neither the school district nor the teacher will offer new services or resources to be expended on your child unless it is in their best interest. In most cases, you will have to fight for every resource you can get for your child. Do NOT be passive. Educate yourself about your rights and the possible resources available to your child. Talk to other parents in the autism community about the resources their children are receiving. Like many parents, I too at first felt that being profes­sional and “nice” was the best way to get my child “good” services. I thought, “You catch more flies with honey than vinegar.” Unfortunately, this naiveté did not pay off: things only worsened with this approach. It was not until we learned more about our rights as parents and challenged the school system that things improved at all.

Sign in / Sign up

Export Citation Format

Share Document