loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

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.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.15.229.191

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

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

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic