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Assessment of the autism spectrum disorder based on machine learning and social visual attention: a systematic review

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Assessment of the autism spectrum disorder based on machine learning and social visual attention: a systematic review

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dc.contributor.author Minissi, Maria Eleonora es_ES
dc.contributor.author CHICCHI-GIGLIOLI, IRENE ALICE es_ES
dc.contributor.author Mantovani, Fabrizia es_ES
dc.contributor.author Alcañiz Raya, Mariano Luis es_ES
dc.date.accessioned 2022-01-30T19:06:19Z
dc.date.available 2022-01-30T19:06:19Z
dc.date.issued 2021-06 es_ES
dc.identifier.issn 0162-3257 es_ES
dc.identifier.uri http://hdl.handle.net/10251/180361
dc.description.abstract [EN] 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. es_ES
dc.description.sponsorship The authors have no relevant financial or non-financial interests to disclose. This work was supported by the Spanish Ministry of Economy, Industry, and Competitiveness funded project "Immersive Virtual Environment for the Evaluation and Training of Children with Autism Spectrum Disorder: T Room" (IDI-20170912). This work was also supported by the Spanish Ministry of Science and Innovation funded project "T-EYE: Monitoring system for children with ASD based on artificial intelligence and physiological measures" (IDI-20201146) es_ES
dc.language Inglés es_ES
dc.publisher Springer-Verlag es_ES
dc.relation.ispartof Journal of Autism and Developmental Disorders es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Autism spectrum disorder es_ES
dc.subject Machine learning es_ES
dc.subject Eye tracking es_ES
dc.subject Social visual attention es_ES
dc.subject Assessment es_ES
dc.subject Classifcation es_ES
dc.subject.classification EXPRESION GRAFICA EN LA INGENIERIA es_ES
dc.title Assessment of the autism spectrum disorder based on machine learning and social visual attention: a systematic review es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s10803-021-05106-5 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//IDI-20201146//T-EYE: Monitoring system for children with ASD based on artificial intelligence and physiological measures/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//IDI-20170912//Entorno virtual inmersivo para la evaluación y capacitación de niños con trastorno del espectro autista: T Room/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Gráfica - Departament d'Enginyeria Gràfica es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Interuniversitario de Investigación en Bioingeniería y Tecnología Orientada al Ser Humano - Institut Interuniversitari d'Investigació en Bioenginyeria i Tecnologia Orientada a l'Ésser Humà es_ES
dc.description.bibliographicCitation Minissi, ME.; Chicchi-Giglioli, IA.; Mantovani, F.; Alcañiz Raya, ML. (2021). Assessment of the autism spectrum disorder based on machine learning and social visual attention: a systematic review. Journal of Autism and Developmental Disorders. 1-16. https://doi.org/10.1007/s10803-021-05106-5 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1007/s10803-021-05106-5 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 16 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.identifier.pmid 34101081 es_ES
dc.relation.pasarela S\439310 es_ES
dc.contributor.funder Ministerio de Ciencia e Innovación es_ES
dc.contributor.funder Ministerio de Economía, Industria y Competitividad es_ES
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