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A predictive model for chinese children with developmental dyslexia—Based on a genetic algorithm optimized back-propagation neural network
Wang, Runzhou1,2; Bi, Hong-Yan1,2
First AuthorWang, Runzhou
Correspondent Emailrunzhouwang@163.com (R. Wang) ; bihy@psych.ac.cn (H.-Y. Bi)
Contribution Rank1
Abstract

The identification or the diagnosis of developmental dyslexia has long been a difficult issue, and traditional logistic regression predictive models have some defects. This study established a genetic algorithm optimized back-propagation neural network model to predict whether Chinese children have dyslexia based on data from 399 children (187 children with dyslexia and 212 typically developing children, 3rd-6th graders, aged 7-13 years). The model achieved an overall prediction accuracy of approximately 94%. Moreover, reading accuracy was the strongest factor in predicting Chinese dyslexic children, and phonological awareness, the accuracy rate of pseudocharacters, morphological awareness, reading fluency, rapid digit naming, and the reaction times of noncharacters also made important contributions to the prediction. In summary, the model we established in this study had an excellent predictive capability regarding Chinese children with/without developmental dyslexia. Furthermore, the genetic algorithm optimized back-propagation neural network model that substantially improves the prediction accuracy of Chinese dyslexia, has the potential to direct more targeted prevention and treatment strategies, and lay the foundation for the artificial intelligence expert diagnosis system for Chinese dyslexia.

KeywordChinese children Developmental dyslexia Predictive model Back-propagation neural network Genetic algorithm
2022
Language英语
DOI10.1016/j.eswa.2021.115949
Source PublicationExpert Systems with Applications
ISSN09574174
Volume187Issue:1
Subtype实证研究
Indexed BySCI ; EI
WoS QuartileQ1
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.psych.ac.cn/handle/311026/40097
Collection中国科学院行为科学重点实验室
Affiliation1.CAS Key Laboratory of Behavioral Science, Center for Brain Science and Learning Difficulties, Institute of Psychology, Chinese Academy of Sciences, Beijing; 100101, China
2.Department of Psychology, University of Chinese Academy of Sciences, Beijing; 100049, China
First Author AffilicationInstitute of Psychology, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Wang, Runzhou,Bi, Hong-Yan. A predictive model for chinese children with developmental dyslexia—Based on a genetic algorithm optimized back-propagation neural network[J]. Expert Systems with Applications,2022,187(1).
APA Wang, Runzhou,&Bi, Hong-Yan.(2022).A predictive model for chinese children with developmental dyslexia—Based on a genetic algorithm optimized back-propagation neural network.Expert Systems with Applications,187(1).
MLA Wang, Runzhou,et al."A predictive model for chinese children with developmental dyslexia—Based on a genetic algorithm optimized back-propagation neural network".Expert Systems with Applications 187.1(2022).
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