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  • Open Access

    ARTICLE

    Research on the Effect of Dance Therapy on Improving Social Communication Ability of Children with Autism

    Xiaorui Cui1, Shan Wang2,*

    International Journal of Mental Health Promotion, Vol.26, No.5, pp. 407-416, 2024, DOI:10.32604/ijmhp.2023.030135 - 30 May 2024

    Abstract Research motivation: Through the 12 weeks dance therapy intervention for children with autism, the purpose is to explore the intervention model of dance therapy for children with autism and the changes in motor ability, social ability, and communication ability of children with autism after dance therapy intervention. The results of the research are expected to expand the intervention mode of dance therapy in my country and provide practical reference for rehabilitation intervention of children with autism. Research methods: 24 autistic boys aged 6 to 12 with mild to moderate symptoms were recruited and screened through the Internet… More >

  • Open Access

    ARTICLE

    Facial Image-Based Autism Detection: A Comparative Study of Deep Neural Network Classifiers

    Tayyaba Farhat1,2, Sheeraz Akram3,*, Hatoon S. AlSagri3, Zulfiqar Ali4, Awais Ahmad3, Arfan Jaffar1,2

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 105-126, 2024, DOI:10.32604/cmc.2023.045022 - 30 January 2024

    Abstract Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by significant challenges in social interaction, communication, and repetitive behaviors. Timely and precise ASD detection is crucial, particularly in regions with limited diagnostic resources like Pakistan. This study aims to conduct an extensive comparative analysis of various machine learning classifiers for ASD detection using facial images to identify an accurate and cost-effective solution tailored to the local context. The research involves experimentation with VGG16 and MobileNet models, exploring different batch sizes, optimizers, and learning rate schedulers. In addition, the “Orange” machine learning tool is employed to… More >

  • Open Access

    ARTICLE

    Diagnosis of Autism Spectrum Disorder by Imperialistic Competitive Algorithm and Logistic Regression Classifier

    Shabana R. Ziyad1,*, Liyakathunisa2, Eman Aljohani2, I. A. Saeed3

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1515-1534, 2023, DOI:10.32604/cmc.2023.040874 - 29 November 2023

    Abstract Autism spectrum disorder (ASD), classified as a developmental disability, is now more common in children than ever. A drastic increase in the rate of autism spectrum disorder in children worldwide demands early detection of autism in children. Parents can seek professional help for a better prognosis of the child’s therapy when ASD is diagnosed under five years. This research study aims to develop an automated tool for diagnosing autism in children. The computer-aided diagnosis tool for ASD detection is designed and developed by a novel methodology that includes data acquisition, feature selection, and classification phases.… More >

  • Open Access

    REVIEW

    The Electrophysiology of Semantic Processing in Individuals with Autism Spectrum Disorder: A Meta-Analysis

    Danfeng Yuan1, Xiangyun Yang1, Lijuan Yang1, Zhanjiang Li1,2,*

    International Journal of Mental Health Promotion, Vol.25, No.10, pp. 1067-1079, 2023, DOI:10.32604/ijmhp.2023.041430 - 03 November 2023

    Abstract Language difficulties vary widely among people with autism spectrum disorder (ASD). However, the semantic processing of autistic person and its underlying electrophysiological mechanism are still unclear. This meta-analysis aimed to explore the disturbance of semantic processing in patients with ASD. PubMed, Web of Science, and Embase were searched for event-related potential (ERP) studies on semantic processing in autistic people published in English before September 01, 2022. Pooled estimates were calculated by fixed-effects or random-effects models according to the heterogeneity using Comprehensive Meta-Analysis 2.0. The potential moderators were explored by meta-regression and subgroup analysis. This meta-analysis… More >

  • Open Access

    ARTICLE

    Eye-Tracking Based Autism Spectrum Disorder Diagnosis Using Chaotic Butterfly Optimization with Deep Learning Model

    Tamilvizhi Thanarajan1, Youseef Alotaibi2, Surendran Rajendran3,*, Krishnaraj Nagappan4

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1995-2013, 2023, DOI:10.32604/cmc.2023.039644 - 30 August 2023

    Abstract Autism spectrum disorder (ASD) can be defined as a neurodevelopmental condition or illness that can disturb kids who have heterogeneous characteristics, like changes in behavior, social disabilities, and difficulty communicating with others. Eye tracking (ET) has become a useful method to detect ASD. One vital aspect of moral erudition is the aptitude to have common visual attention. The eye-tracking approach offers valuable data regarding the visual behavior of children for accurate and early detection. Eye-tracking data can offer insightful information about the behavior and thought processes of people with ASD, but it is important to… More >

  • Open Access

    REVIEW

    Video-Based Interventions for Adolescents and Young Adults with Autism Spectrum Disorder: A Systematic Review

    Mohammed Al Jaffal*

    International Journal of Mental Health Promotion, Vol.25, No.8, pp. 881-890, 2023, DOI:10.32604/ijmhp.2023.028982 - 06 July 2023

    Abstract Many individuals with autism spectrum disorder (ASD) experience delays in the development of social and communications skills, which can limit their opportunities in higher education and employment resulting in an overall negative impact to their quality of life. This systematic review identifies 15 studies that explored the effectiveness of Video-Based Interventions (VBIs) for those with ASD during the critical years of adolescence and young adulthood. The 15 studies described herein found this to be an effective intervention for this population for the improvement of their vocational, daily living, and academic skills. In addition, VBIs allow… More >

  • Open Access

    ARTICLE

    Automated Autism Spectral Disorder Classification Using Optimal Machine Learning Model

    Hanan Abdullah Mengash1, Hamed Alqahtani2, Mohammed Maray3, Mohamed K. Nour4, Radwa Marzouk1, Mohammed Abdullah Al-Hagery5, Heba Mohsen6, Mesfer Al Duhayyim7,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5251-5265, 2023, DOI:10.32604/cmc.2023.032729 - 28 December 2022

    Abstract Autism Spectrum Disorder (ASD) refers to a neuro-disorder where an individual has long-lasting effects on communication and interaction with others. Advanced information technology which employs artificial intelligence (AI) model has assisted in early identify ASD by using pattern detection. Recent advances of AI models assist in the automated identification and classification of ASD, which helps to reduce the severity of the disease. This study introduces an automated ASD classification using owl search algorithm with machine learning (ASDC-OSAML) model. The proposed ASDC-OSAML model majorly focuses on the identification and classification of ASD. To attain this, the More >

  • Open Access

    ARTICLE

    Early Detection of Autism in Children Using Transfer Learning

    Taher M. Ghazal1,2, Sundus Munir3,4, Sagheer Abbas3, Atifa Athar5, Hamza Alrababah1, Muhammad Adnan Khan6,*

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 11-22, 2023, DOI:10.32604/iasc.2023.030125 - 29 September 2022

    Abstract Autism spectrum disorder (ASD) is a challenging and complex neuro-development syndrome that affects the child’s language, speech, social skills, communication skills, and logical thinking ability. The early detection of ASD is essential for delivering effective, timely interventions. Various facial features such as a lack of eye contact, showing uncommon hand or body movements, babbling or talking in an unusual tone, and not using common gestures could be used to detect and classify ASD at an early stage. Our study aimed to develop a deep transfer learning model to facilitate the early detection of ASD based More >

  • Open Access

    ARTICLE

    Jellyfish Search Optimization with Deep Learning Driven Autism Spectrum Disorder Classification

    S. Rama Sree1, Inderjeet Kaur2, Alexey Tikhonov3, E. Laxmi Lydia4, Ahmed A. Thabit5, Zahraa H. Kareem6, Yousif Kerrar Yousif7, Ahmed Alkhayyat8,*

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 2195-2209, 2023, DOI:10.32604/cmc.2023.032586 - 22 September 2022

    Abstract Autism spectrum disorder (ASD) is regarded as a neurological disorder well-defined by a specific set of problems associated with social skills, recurrent conduct, and communication. Identifying ASD as soon as possible is favourable due to prior identification of ASD permits prompt interferences in children with ASD. Recognition of ASD related to objective pathogenic mutation screening is the initial step against prior intervention and efficient treatment of children who were affected. Nowadays, healthcare and machine learning (ML) industries are combined for determining the existence of various diseases. This article devises a Jellyfish Search Optimization with Deep… More >

  • Open Access

    ARTICLE

    An Intelligent Hybrid Ensemble Gene Selection Model for Autism Using DNN

    G. Anurekha*, P. Geetha

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3049-3064, 2023, DOI:10.32604/iasc.2023.029127 - 17 August 2022

    Abstract Autism Spectrum Disorder (ASD) is a complicated neurodevelopmental disorder that is often identified in toddlers. The microarray data is used as a diagnostic tool to identify the genetics of the disorder. However, microarray data is large and has a high volume. Consequently, it suffers from the problem of dimensionality. In microarray data, the sample size and variance of the gene expression will lead to overfitting and misclassification. Identifying the autism gene (feature) subset from microarray data is an important and challenging research area. It has to be efficiently addressed to improve gene feature selection and… More >

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