Cited by 297Autism Spectrum Disorder ResearchFace Recognition and PerceptionFace recognition and analysis

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Identifying children with autism spectrum disorder based on their face processing abnormality: A machine learning framework

Liu, Wenbo, Li, Ming, Yi, Li·2016·Autism Research

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Abstract

The atypical face scanning patterns in individuals with Autism Spectrum Disorder (ASD) has been repeatedly discovered by previous research. The present study examined whether their face scanning patterns could be potentially useful to identify children with ASD by adopting the machine learning algorithm for the classification purpose. Particularly, we applied the machine learning method to analyze an eye movement dataset from a face recognition task [Yi et al., 2016], to classify children with and without ASD. We evaluated the performance of our model in terms of its accuracy, sensitivity, and specificity of classifying ASD. Results indicated promising evidence for applying the machine learning algorithm based on the face scanning patterns to identify children with ASD, with a maximum classification accuracy of 88.51%. Nevertheless, our study is still preliminary with some constraints that may apply in the clinical practice. Future research should shed light on further valuation of our method and contribute to the development of a multitask and multimodel approach to aid the process of early detection and diagnosis of ASD. Autism Res 2016, 9: 888–898 . © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

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Authors: Liu, W., Li, M., & Yi, L.
Affiliations: Sun Yat-sen University (CN)
Peking University (CN)
Corresponding author: Li, Ming
Yi, Li
ORCID: Liu, Wenbo
Li, Ming
Yi, Li
Venue: Autism Research
Publisher: Wiley
Published: 2016-04
Volume: 9
Issue: 8
Pages: 888-898
ISSN: 1939-3792 (ISSN-L)
1939-3806
DOI: 10.1002/aur.1615
OpenAlex: W2328587688
Semantic Scholar: 05a9d8caa91ac2aa7641c96a4218c1eed5f4684f
Cited by: 297
References: 36
Citations by year: 2026: 19 · 2025: 33 · 2024: 50 · 2023: 35 · 2022: 37 · 2021: 45 · 2020: 33 · 2019: 26 · 2018: 11 · 2017: 8
FWCI: 9.55
Type: journal article
Language: en
Open access: closed
Licence: onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations: Autism Research (publishedVersion)
PubMed (publishedVersion)
Funders: National Natural Science Foundation of China (31571135, 31200779, 61401524)
Science and Technology Foundation of Guizhou Province (2014A030313123)
Topics: Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face recognition and analysis
Keywords: autism spectrum disorder, face processing, eye movement patterns, facial scanning, ASD classification, children, early diagnosis, machine learning classification
MeSH terms: Autism Spectrum Disorder, Machine Learning, Algorithms, Child, Child, Preschool, China, Eye Movements, Face, Female, Humans, Male, Sensitivity and Specificity, Visual Perception, Reproducibility of Results, Recognition, Psychology

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Identifying children with autism spectrum disorder based on their face processing abnormality: A machine learning framework

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