Investigating autism etiology and heterogeneity by decision tree algorithm

Hassan, Mariam M.; Mokhtar, Hoda M. O.

doi:10.1016/j.imu.2019.100215

Cited by 48 publications

(18 citation statements)

References 26 publications

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“…Combined knowledge and competence of interdisciplinary team specialists provides optimal conditions for the successful development of a child, his/her adaptation and social interactions in the community, as well as allowing them to overcome difficulties including those related to the heterogeneity of disorders [ 66 , 70 , 71 ]. Unfortunately, the results obtained from our research indicated poor development of interdisciplinary interactions among specialists in Russia.…”

Section: Discussionmentioning

confidence: 99%

Health care providers’ awareness on medical management of children with autism spectrum disorder: cross-sectional study in Russia

et al. 2022

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Background Autism spectrum disorder (ASD) is a complex developmental range of conditions that involves difficulties with social interaction and restricted/repetitive behaviors. Unfortunately, health care providers often experience difficulties in diagnosis and management of individuals with ASD, and may have no knowledge about possible ways to overcome barriers in ASD patient interactions in healthcare settings. At the same time, the provision of appropriate medical services can have positive effects on habilitative progress, functional outcome, life expectancy and quality of life for individuals with ASD. Methods This online survey research study evaluated the awareness and experience of students/residents (n = 247) and physicians (n = 100) in the medical management of children with ASD. It also gathered the views and experiences of caregivers to children with ASD (n = 158), all based in Russia. Results We have established that the Russian medical community has limited ASD knowledge among providers, and have suggested possible reasons for this. Based on results from online surveys completed by students/residents, non-psychiatric physicians, and caregivers of children diagnosed with ASD, the main problems pertaining to medical management of individuals with ASD were identified. Possible problem solving solutions within medical practice were proposed. Conclusions The results from this study should be considered when implementing measures to improve healthcare practices, and when developing models for effective medical management, due to start not only in Russia but also in a number of other countries.

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Section: Discussionmentioning

confidence: 99%

Health care providers’ awareness on medical management of children with autism spectrum disorder: cross-sectional study in Russia

et al. 2022

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“…Further studies using neuroimaging methods and using both time pressure and non-timed conditions could provide a more direct link between atypical processing and socio-emotional behavioural difficulties in children with ASD. Moreover, it is important to note that people with ASD are a heterogeneous population, with no unifying theory to account for the symptoms in the symptom groups as outlined by the DSM-5 ( American Psychiatric Association, 2013 ; Hassan & Mokhtar, 2019 ). It means that the underlying mechanisms of any social difficulties might be variable, and the conclusions drawn from a small sample study should be regarded as exploratory.…”

Section: Discussionmentioning

confidence: 99%

Atypical Facial Emotion Recognition in Children with Autism Spectrum Disorders: Exploratory Analysis on the Role of Task Demands

2021

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People with autism spectrum disorders (ASDs) have difficulty with socio-emotional functioning; however, research on facial emotion recognition (FER) remains inconclusive. Individuals with ASD might be using atypical compensatory mechanisms that are exhausted in more complex tasks. This study compared response accuracy and speed on a forced-choice FER task using neutral, happy, sad, disgust, anger, fear and surprise expressions under both timed and non-timed conditions in children with and without ASD ( n = 18). The results showed that emotion recognition accuracy was comparable in the two groups in the non-timed condition. However, in the timed condition, children with ASD were less accurate in identifying anger and surprise compared to children without ASD. This suggests that people with ASD have atypical processing of anger and surprise that might become challenged under time pressure. Understanding these atypical processes, and the environmental factors that challenge them, could be beneficial in supporting socio-emotional functioning in people ASD.

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“…Hassan & Mokhtar (2019) worked on decision tree method were utilized to analyze related factors in datasets obtained from the National Database for Autism Research (NDAR) consisting of nearly 3000 individuals. The Decision Tree Classifier from scikit-learn, ADTree, CDT, J48, and LADTree classifiers have used, The experimental outcome they obtained the accuracy 90% using the decision tree classifiers (Hassan & Mokhtar, 2019). Diabat et al (2019) worked on the classifiers C4.5, PART, RIPPER and Voted Perceptron and Ensemble Classification for Autism Screening (ECAS).…”

Section: Related Workmentioning

confidence: 99%

Classification of Autistic Spectrum Disorder Using Deep Neural Network With Particle Swarm Optimization

Sahu¹,

Verma

2021

International Journal of Computer Vision and Image Processing

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In this paper, Feature Selection Technique (FST) namely Particle Swarm Optimization (PSO) has been used. The filter based PSO is a search method with Correlation-based Feature Selection (CBFS) as a fitness function. The FST has two key goals of improving classification efficiency and reducing feature counts. Artificial Neural Network (ANN) Based Multilayer Perceptron Network (MLP) and Deep Learning (DL) have been considered the classification methods on 2 benchmark Autistic Spectrum Disorder (ASD) dataset. The experimental result was compared to the non-reduced features and reduced feature of ASD datasets. The reduced feature give up enhanced results in both classifiers MLP and DL. In addition, an experimental study on the exhibitions of these methodologies has been conducted. Finally, a new trend of PSO-MLP and PSO-DL based classification model is proposed.

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Investigating autism etiology and heterogeneity by decision tree algorithm

Cited by 48 publications

References 26 publications

Health care providers’ awareness on medical management of children with autism spectrum disorder: cross-sectional study in Russia

Health care providers’ awareness on medical management of children with autism spectrum disorder: cross-sectional study in Russia

Atypical Facial Emotion Recognition in Children with Autism Spectrum Disorders: Exploratory Analysis on the Role of Task Demands

Classification of Autistic Spectrum Disorder Using Deep Neural Network With Particle Swarm Optimization

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