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Machine learning-based early diagnosis of autism according to eye movements of real and artificial faces scanning

文献类型：期刊论文

作者Meng, Fanchao4,5,6,7; Li, Fenghua3; Wu, Shuxian4,5; Yang, Tingyu4,5; Xiao, Zhou2; Zhang, Yujian1; Liu, Zhengkui3; Lu, Jianping2; Luo, Xuerong4,5
刊名FRONTIERS IN NEUROSCIENCE
出版日期2023-09-15
卷号17页码:10
关键词autism spectrum disorder eye-tracking cartoon character machine learning random forest
DOI10.3389/fnins.2023.1170951
通讯作者Lu, Jianping(szlujianping@126.com) ; Luo, Xuerong(luoxuerong@csu.edu.cn)
英文摘要BackgroundStudies on eye movements found that children with autism spectrum disorder (ASD) had abnormal gaze behavior to social stimuli. The current study aimed to investigate whether their eye movement patterns in relation to cartoon characters or real people could be useful in identifying ASD children.MethodsEye-tracking tests based on videos of cartoon characters and real people were performed for ASD and typically developing (TD) children aged between 12 and 60 months. A three-level hierarchical structure including participants, events, and areas of interest was used to arrange the data obtained from eye-tracking tests. Random forest was adopted as the feature selection tool and classifier, and the flattened vectors and diagnostic information were used as features and labels. A logistic regression was used to evaluate the impact of the most important features.ResultsA total of 161 children (117 ASD and 44 TD) with a mean age of 39.70 +/- 12.27 months were recruited. The overall accuracy, precision, and recall of the model were 0.73, 0.73, and 0.75, respectively. Attention to human-related elements was positively related to the diagnosis of ASD, while fixation time for cartoons was negatively related to the diagnosis.ConclusionUsing eye-tracking techniques with machine learning algorithms might be promising for identifying ASD. The value of artificial faces, such as cartoon characters, in the field of ASD diagnosis and intervention is worth further exploring.
收录类别SCI
WOS关键词SPECTRUM DISORDER ; SOCIAL ATTENTION ; CHILDREN ; LOOKING ; IMAGES ; ASD
资助项目This work was supported by Youth Talent Training Green Seedling Program of Beijing Hospital Management Center (No. QML20231906 to FM), Shenzhen Fund for Guangdong Provincial High-level Clinical Key Specialties (No. SZGSP013 to JL), National Key Ramp;D P[QML20231906] ; Youth Talent Training Green Seedling Program of Beijing Hospital Management Center[SZGSP013] ; Shenzhen Fund for Guangdong Provincial High-level Clinical Key Specialties[2017YFC1309900] ; National Key Ramp;D Program of China[2019SK2081] ; Key Research and Development Program of Hunan Province
WOS研究方向Neurosciences & Neurology
语种英语
出版者FRONTIERS MEDIA SA
WOS记录号WOS:001076615800001
资助机构This work was supported by Youth Talent Training Green Seedling Program of Beijing Hospital Management Center (No. QML20231906 to FM), Shenzhen Fund for Guangdong Provincial High-level Clinical Key Specialties (No. SZGSP013 to JL), National Key Ramp;D P ; Youth Talent Training Green Seedling Program of Beijing Hospital Management Center ; Shenzhen Fund for Guangdong Provincial High-level Clinical Key Specialties ; National Key Ramp;D Program of China ; Key Research and Development Program of Hunan Province
源URL[http://ir.psych.ac.cn/handle/311026/46131]  
专题心理研究所_中国科学院心理健康重点实验室
通讯作者Lu, Jianping; Luo, Xuerong
作者单位1.Sichuan Canc Hosp & Inst, Sichuan Canc Ctr, Chengdu, Sichuan, Peoples R China
2.Kangning Hosp Shenzhen, Shenzhen Mental Hlth Ctr, Dept Child Psychiat, Shenzhen, Guangdong, Peoples R China
3.Chinese Acad Sci, Key Lab Mental Hlth, Inst Psychol, Beijing, Peoples R China
4.Cent South Univ, Natl Clin Res Ctr Mental Disorders, Xiangya Hosp 2, Changsha, Hunan, Peoples R China
5.Cent South Univ, Xiangya Hosp 2, Dept Psychiat, Changsha, Hunan, Peoples R China
6.Capital Med Univ, Beijing Anding Hosp, Beijing Key Lab Mental Disorders, Beijing, Peoples R China
7.Capital Med Univ, Beijing Anding Hosp, Natl Clin Res Ctr Mental Disorders, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Meng, Fanchao,Li, Fenghua,Wu, Shuxian,et al. Machine learning-based early diagnosis of autism according to eye movements of real and artificial faces scanning[J]. FRONTIERS IN NEUROSCIENCE,2023,17:10.
APA Meng, Fanchao.,Li, Fenghua.,Wu, Shuxian.,Yang, Tingyu.,Xiao, Zhou.,...&Luo, Xuerong.(2023).Machine learning-based early diagnosis of autism according to eye movements of real and artificial faces scanning.FRONTIERS IN NEUROSCIENCE,17,10.
MLA Meng, Fanchao,et al."Machine learning-based early diagnosis of autism according to eye movements of real and artificial faces scanning".FRONTIERS IN NEUROSCIENCE 17(2023):10.

入库方式： OAI收割

来源：心理研究所

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