首页|Development of a visual attention based decision support system for autism spectrum disorder screening

Development of a visual attention based decision support system for autism spectrum disorder screening

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Visual attention of young children with autism spectrum disorder (ASD) has been well documented in the literature for the past 20 years. In this study, we developed a Decision Support System (DSS) that uses machine learning (ML) techniques to identify young children with ASD from typically developing (TD) children. Study participants included 26 to 36 months old young children with ASD (n = 61) and TD children (n = 72). The results showed that the proposed DSS achieved up to 87.5% success rate in the early assessment of ASD in young children. Findings suggested that visual attention is a unique, promising biomarker for early assessment of ASD. Study results were discussed, and suggestions for future research were provided.

Autism spectrum disordersEye trackingVisual attentionScreeningMachine learningBiomarkerSOCIAL ATTENTIONCIRCUMSCRIBED INTERESTSEARLY IDENTIFICATIONEYE-TRACKINGCHILDRENTODDLERSPATTERNSADULTSBRAINIMPAIRMENT

Ozdemir, Selda、Akin-Bulbul, Isik、Kok, Ibrahim、Ozdemir, Suat

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Hacettepe Educ Fac,Hacettepe Univ

Gazi Educ Fac,Gazi Univ

Engn Fac,Pamukkale Univ

Engn Fac,Hacettepe Univ

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2022

International journal of psychophysiology

International journal of psychophysiology

SCI
ISSN:0167-8760
年,卷(期):2022.173
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