Rehabilitation Educational Design for Children with Autism Based on the Radial Basis Function Neural Network

Qi, Yueer; Han, Jia-Xuan

doi:10.1155/2021/2961546

Cited by 4 publications

(4 citation statements)

References 22 publications

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“…Diagnosis of autism spectrum disorder with artificial intelligence: Convolutional neural networks were used to develop an automated facial expression recognition therapeutic tool on mobile devices for children with autism [63]. A method based on a radial basis function neural network was used to support the design and evaluation of educational toys for children with autism [64].…”

Section: Deductive Content Analysis Of the Most Prolific Machine Lear...mentioning

confidence: 99%

Artificial Intelligence and Pediatrics: Synthetic Knowledge Synthesis

Završnik,

Kokol,

Žlahtič

et al. 2024

Electronics

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The first publication on the use of artificial intelligence (AI) in pediatrics dates back to 1984. Since then, research on AI in pediatrics has become much more popular, and the number of publications has largely increased. Consequently, a need for a holistic research landscape enabling researchers and other interested parties to gain insights into the use of AI in pediatrics has arisen. To fill this gap, a novel methodology, synthetic knowledge synthesis (SKS), was applied. Using SKS, we identified the most prolific countries, institutions, source titles, funding agencies, and research themes and the most frequently used AI algorithms and their applications in pediatrics. The corpus was extracted from the Scopus (Elsevier, The Netherlands) bibliographic database and analyzed using VOSViewer, version 1.6.20. Done An exponential growth in the literature was observed in the last decade. The United States, China, and Canada were the most productive countries. Deep learning was the most used machine learning algorithm and classification, and natural language processing was the most popular AI approach. Pneumonia, epilepsy, and asthma were the most targeted pediatric diagnoses, and prediction and clinical decision making were the most frequent applications.

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Section: Deductive Content Analysis Of the Most Prolific Machine Lear...mentioning

confidence: 99%

Artificial Intelligence and Pediatrics: Synthetic Knowledge Synthesis

Završnik,

Kokol,

Žlahtič

et al. 2024

Electronics

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“…Designers should start from the rehabilitation needs of autistic children, fully respect the psychological characteristics of autistic children, and understand the behavior of patients ( Mazurek et al, 2020 ). Qi, Han & Yin (2021) believe it is necessary to design an educational rehabilitation platform for children with autism.…”

Section: Introductionmentioning

confidence: 99%

Automatic design and optimization of educational space for autistic children based on deep neural network and affordance theory

Chu

2023

PeerJ Computer Science

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In recent years, the incidence of autistic children has shown rapid growth worldwide. The rapid development of education and rehabilitation institutions for autistic children is of great significance to the rehabilitation of this group. However, the research on indoor space environments and functional facilities for autistic children in China is still in its infancy. Reasonably and effectively, zoning the education and rehabilitation space for autistic children can promote better communication and learning between autistic children and rehabilitation therapists and effectively promote the rehabilitation progress of autistic children. However, the existing education and rehabilitation space for autistic children has some problems, such as unscientific indoor partition, indoor space layouts mainly relying on manual work, heavy workload and low efficiency. Therefore, it is of great research value and practical significance to explore the intuitive design and optimization of the education and rehabilitation space layout for autistic children. This study first evaluates and optimizes the educational space for autistic children based on the affordability theory. Then, this study proposes a layout recommendation algorithm based on deep learning, which is used to improve the layout efficiency of the education and rehabilitation space for autistic children and realize real-time online layout. The scene information is digitized in binary code. The segmentation and layout network models are constructed through bidirectional long short-term memory (LSTM) to discover the long segment pre-segmentation of house type and obtain the layout results. The word embedding algorithm is used to abstract the cross features between each vector segment, and the dimension of the feature matrix is reduced to improve the speed and accuracy of the layout scheme recommendation. The experimental results show that our method can learn the design rules from the data set and has achieved better results than the existing methods. This study provides an adequate theoretical basis and design reference for the research of residential education space for autistic children.

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“…This article has been retracted by Hindawi following an investigation undertaken by the publisher [ 1 ]. This investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process: Discrepancies in scope Discrepancies in the description of the research reported Discrepancies between the availability of data and the research described Inappropriate citations Incoherent, meaningless and/or irrelevant content included in the article Peer-review manipulation …”

mentioning

confidence: 99%

“…Tis article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. Tis investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”

mentioning

confidence: 99%

Retracted: Rehabilitation Educational Design for Children with Autism Based on the Radial Basis Function Neural Network

Healthcare Engineering

2023

Journal of Healthcare Engineering

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Rehabilitation Educational Design for Children with Autism Based on the Radial Basis Function Neural Network

Cited by 4 publications

References 22 publications

Artificial Intelligence and Pediatrics: Synthetic Knowledge Synthesis

Artificial Intelligence and Pediatrics: Synthetic Knowledge Synthesis

Automatic design and optimization of educational space for autistic children based on deep neural network and affordance theory

Retracted: Rehabilitation Educational Design for Children with Autism Based on the Radial Basis Function Neural Network

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