The assessment of autism spectrum disorder (ASD) is based on semi-structured procedures addressed to children and caregivers. Such methods rely on the evaluation of behavioural symptoms rather than on the objective evaluation of psychophysiological underpinnings. Advances in research provided evidence of modern procedures for the early assessment of ASD, involving both machine learning (ML) techniques and biomarkers, as eye movements (EM) towards social stimuli. This systematic review provides a comprehensive discussion of 11 papers regarding the early assessment of ASD based on ML techniques and children's social visual attention (SVA). Evidences suggest ML as a relevant technique for the early assessment of ASD, which might represent a valid biomarker-based procedure to objectively make diagnosis. Limitations and future directions are discussed.

Minissi, M. E., Chicchi Giglioli, I. A. M., Mantovani, F., Alcañiz Raya, M., Assessment of the Autism Spectrum Disorder Based on Machine Learning and Social Visual Attention: A Systematic Review, <<JOURNAL OF AUTISM AND DEVELOPMENTAL DISORDERS>>, N/A; 52 (N/A): N/A-N/A. [doi:10.1007/s10803-021-05106-5] [https://hdl.handle.net/10807/268256]

Assessment of the Autism Spectrum Disorder Based on Machine Learning and Social Visual Attention: A Systematic Review

Chicchi Giglioli, Irene Alice Margherita;
2021

Abstract

The assessment of autism spectrum disorder (ASD) is based on semi-structured procedures addressed to children and caregivers. Such methods rely on the evaluation of behavioural symptoms rather than on the objective evaluation of psychophysiological underpinnings. Advances in research provided evidence of modern procedures for the early assessment of ASD, involving both machine learning (ML) techniques and biomarkers, as eye movements (EM) towards social stimuli. This systematic review provides a comprehensive discussion of 11 papers regarding the early assessment of ASD based on ML techniques and children's social visual attention (SVA). Evidences suggest ML as a relevant technique for the early assessment of ASD, which might represent a valid biomarker-based procedure to objectively make diagnosis. Limitations and future directions are discussed.
2021
Inglese
Minissi, M. E., Chicchi Giglioli, I. A. M., Mantovani, F., Alcañiz Raya, M., Assessment of the Autism Spectrum Disorder Based on Machine Learning and Social Visual Attention: A Systematic Review, <<JOURNAL OF AUTISM AND DEVELOPMENTAL DISORDERS>>, N/A; 52 (N/A): N/A-N/A. [doi:10.1007/s10803-021-05106-5] [https://hdl.handle.net/10807/268256]
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