K. Chola Raja^1,*, S. Kannimuthu²

Computer Systems Science and Engineering, Vol.44, No.1, pp. 741-755, 2023, DOI:10.32604/csse.2023.025331

Abstract Autism Spectrum Disorder (ASD) requires a precise diagnosis in order to be managed and rehabilitated. Non-invasive neuroimaging methods are disease markers that can be used to help diagnose ASD. The majority of available techniques in the literature use functional magnetic resonance imaging (fMRI) to detect ASD with a small dataset, resulting in high accuracy but low generality. Traditional supervised machine learning classification algorithms such as support vector machines function well with unstructured and semi structured data such as text, images, and videos, but their performance and robustness are restricted by the size of the accompanying training data. Deep learning on… More >

Mengxian Zhao¹, Yonghao You², Jinming Li³, Sean Healy⁴, Alyx Taylor⁵, Zhihao Zhang³, Linlin Li⁶, Liye Zou^7,*

International Journal of Mental Health Promotion, Vol.24, No.4, pp. 475-489, 2022, DOI:10.32604/ijmhp.2022.021361

Abstract Therapeutic horseback riding (THR) as an animal-assisted intervention is one of the innovative approaches emerging in the treatment for children with autism spectrum disorder (ASD). The current study was designed to investigate the effects of a 12-week, twice a week THR program on motor skills in sixty-eight children with ASD aged 5–10 years old. All participants selected met the DSM-V criteria for ASD, and a total of fifty-three participants completed the study. A randomized controlled trial design was utilized for the study. Data was collected via a pre-THR test, interim-THR test, and post-THR test to investigate the possible changes in… More >

Yin Liang^1,*, Gaoxu Xu¹, Sadaqat ur Rehman²

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4645-4661, 2022, DOI:10.32604/cmc.2022.026999

Abstract Whole brain functional connectivity (FC) patterns obtained from resting-state functional magnetic resonance imaging (rs-fMRI) have been widely used in the diagnosis of brain disorders such as autism spectrum disorder (ASD). Recently, an increasing number of studies have focused on employing deep learning techniques to analyze FC patterns for brain disease classification. However, the high dimensionality of the FC features and the interpretation of deep learning results are issues that need to be addressed in the FC-based brain disease classification. In this paper, we proposed a multi-scale attention-based deep neural network (MSA-DNN) model to classify FC patterns for the ASD diagnosis.… More >

A. Saranya^1,*, R. Anandan²

Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 1167-1182, 2022, DOI:10.32604/iasc.2022.023445

Abstract Hereditary Autism Spectrum Disorder (ASD) is a neuron disorder that affects a person's ability for communication, interaction, and also behaviors. Diagnostics of autism are available throughout all stages of life, from infancy through adolescence and adulthood. Facial Emotions detection is considered to be the most parameter for the detection of Autismdisorders among the different categories of people. Propelled with a machine and deep learning algorithms, detection of autism disorder using facial emotions has reached a new dimension and has even been considered as the precautionary warning system for caregivers. Since Facial emotions are limited to only seven expressions, detection of… More >

Zhiyuan Sun^1,2, Fabian Herold^3,4, Kelong Cai^1,2, Qian Yu⁵, Xiaoxiao Dong^1,2, Zhimei Liu^1,2, Jinming Li⁶, Aiguo Chen^1,2,* , Liye Zou^7,*

International Journal of Mental Health Promotion, Vol.24, No.2, pp. 143-158, 2022, DOI:10.32604/ijmhp.2022.020075

Abstract In recent years evidence has emerged suggesting that Mini-basketball training program (MBTP) can be an effective intervention method to improve social communication (SC) impairments and restricted and repetitive behaviors (RRBs) in preschool children suffering from autism spectrum disorder (ASD). However, there is a considerable degree if interindividual variability concerning these social outcomes and thus not all preschool children with ASD profit from a MBTP intervention to the same extent. In order to make more accurate predictions which preschool children with ASD can benefit from an MBTP intervention or which preschool children with ASD need additional interventions to achieve behavioral improvements,… More >

MAKOTO NABETANI^1,*, TAKEO MUKAI²

BIOCELL, Vol.46, No.4, pp. 873-879, 2022, DOI:10.32604/biocell.2022.018218

Abstract Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by impairments in social communication, abnormal to absent verbal communication, the presence of repetitive stereotypic verbal and non-verbal behaviors and restricted interests, with onset early in life. We showed cognitive and behavioral characteristics of ASD by impairment of communication, cognition, perception, motor skills, executive function, theory of mind and emotion control. Recently, pathogenesis of immune pathology in the brains of individuals with ASD has been focused. New therapeutic approaches in the viewpoints of immune modulation and microglial function are logical for novel treatments for individuals with ASD. Cell therapies such… More >

Anwer Mustafa Hilal¹, Imène ISSAOUI², Marwa Obayya³, Fahd N. Al-Wesabi⁴, Nadhem NEMRI⁵, Manar Ahmed Hamza^1,*, Mesfer Al Duhayyim⁶, Abu Sarwar Zamani¹

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3853-3867, 2022, DOI:10.32604/cmc.2022.022663

Abstract The abundant existence of both structured and unstructured data and rapid advancement of statistical models stressed the importance of introducing Explainable Artificial Intelligence (XAI), a process that explains how prediction is done in AI models. Biomedical mental disorder, i.e., Autism Spectral Disorder (ASD) needs to be identified and classified at early stage itself in order to reduce health crisis. With this background, the current paper presents XAI-based ASD diagnosis (XAI-ASD) model to detect and classify ASD precisely. The proposed XAI-ASD technique involves the design of Bacterial Foraging Optimization (BFO)-based Feature Selection (FS) technique. In addition, Whale Optimization Algorithm (WOA) with… More >

Anupam Garg¹, Anshu Parashar¹, Dipto Barman², Sahil Jain³, Divya Singhal³, Mehedi Masud⁴, Mohamed Abouhawwash^5,6,*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1459-1471, 2022, DOI:10.32604/cmc.2022.022170

Abstract Autism Spectrum Disorder (ASD) is a developmental disorder whose symptoms become noticeable in early years of the age though it can be present in any age group. ASD is a mental disorder which affects the communicational, social and non-verbal behaviors. It cannot be cured completely but can be reduced if detected early. An early diagnosis is hampered by the variation and severity of ASD symptoms as well as having symptoms commonly seen in other mental disorders as well. Nowadays, with the emergence of deep learning approaches in various fields, medical experts can be assisted in early diagnosis of ASD. It… More >

A. Arunkumar^1,*, D. Surendran²

Computer Systems Science and Engineering, Vol.41, No.1, pp. 389-404, 2022, DOI:10.32604/csse.2022.020256

Abstract Difficulty in communicating and interacting with other people are mainly due to the neurological disorder called autism spectrum disorder (ASD) diseases. These diseases can affect the nerves at any stage of the human being in childhood, adolescence, and adulthood. ASD is known as a behavioral disease due to the appearances of symptoms over the first two years that continue until adulthood. Most of the studies prove that the early detection of ASD helps improve the behavioral characteristics of patients with ASD. The detection of ASD is a very challenging task among various researchers. Machine learning (ML) algorithms still act very… More >

V. Balaji^*, S. Kanaga Suba Raja

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 1301-1315, 2022, DOI:10.32604/iasc.2022.020287

Abstract Autism spectrum disorder (ASD), is a neurological developmental disorder. It affects how people communicate and interact with others, as well as how they behave and learn. The symptoms and signs appear when a child is very young. Derived with increased usage of machine learning procedure in the medicinal analysis investigations. In this paper, our objective is to find out the most significant attributes and automate the process using classification techniques and pattern clustering using K-means clustering. We have analyzed ASD datasets of children towards determining the best performance of classifier for these binary datasets considering recall, precision, accuracy and classification… More >