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Authors: Sara Vecino 1 ; Martín Gonzalez-Rodriguez 1 ; Javier de Andres-Suarez 2 and Daniel Fernandez-Lanvin 1

Affiliations: 1 Department of Computer Science, University of Oviedo, Spain ; 2 Department of Accounting, University of Oviedo, Spain

Keyword(s): Eye Tracker, Automatic System, Diagnosis, Autism Spectrum Disorder, ASD, Machine Learning.

Abstract: Early autism spectrum disorder diagnosis is key to help children and their families sooner and thus, avoiding the high social and economic costs that would be produced other way. The aim of the project is to create a web application available in every health centre that could potentially be used as a previous step in early ASD diagnosis. It would be a fast way of diagnosing, spending almost no resources as it is web based. The system uses machine learning techniques to generate the diagnosis through the analysis of the data obtained from the eye tracker, and every time an evaluation is confirmed, it will be added to the training data set improving the evaluation process.

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Paper citation in several formats:
Vecino, S.; Gonzalez-Rodriguez, M.; de Andres-Suarez, J. and Fernandez-Lanvin, D. (2021). Web Tool based on Machine Learning for the Early Diagnosis of ASD through the Analysis of the Subject’s Gaze. In Proceedings of the 17th International Conference on Web Information Systems and Technologies - WEBIST; ISBN 978-989-758-536-4; ISSN 2184-3252, SciTePress, pages 167-173. DOI: 10.5220/0010715800003058

@conference{webist21,
author={Sara Vecino. and Martín Gonzalez{-}Rodriguez. and Javier {de Andres{-}Suarez}. and Daniel Fernandez{-}Lanvin.},
title={Web Tool based on Machine Learning for the Early Diagnosis of ASD through the Analysis of the Subject’s Gaze},
booktitle={Proceedings of the 17th International Conference on Web Information Systems and Technologies - WEBIST},
year={2021},
pages={167-173},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010715800003058},
isbn={978-989-758-536-4},
issn={2184-3252},
}

TY - CONF

JO - Proceedings of the 17th International Conference on Web Information Systems and Technologies - WEBIST
TI - Web Tool based on Machine Learning for the Early Diagnosis of ASD through the Analysis of the Subject’s Gaze
SN - 978-989-758-536-4
IS - 2184-3252
AU - Vecino, S.
AU - Gonzalez-Rodriguez, M.
AU - de Andres-Suarez, J.
AU - Fernandez-Lanvin, D.
PY - 2021
SP - 167
EP - 173
DO - 10.5220/0010715800003058
PB - SciTePress