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Eye-tracking dataset to support the research on autism spectrum disorder

Cilia, Federica; Carette, Romuald; Elbattah, Mahmoud; Guérin, Jean-Luc; Dequen, Gilles

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Authors

Federica Cilia

Romuald Carette

Mahmoud Elbattah

Jean-Luc Guérin

Gilles Dequen



Abstract

The availability of data is a key enabler for researchers across different disciplines. However, domains, such as healthcare, are still fundamentally challenged by the paucity and imbalance of datasets. Health data could be inaccessible due to a variety of hurdles such as privacy concerns, or lack of sharing incentives. In this regard, this study aims to publish an eye-tracking dataset developed for the purpose of autism diagnosis. Eye-tracking methods are used intensively in that context, whereas abnormalities of the eye gaze are largely recognised as the hallmark of autism. As such, it is believed that the dataset can allow for developing useful applications or discovering interesting insights. As well, Machine Learning is a potential application for developing diagnostic models that can help detect autism at an early stage of development.

Citation

Cilia, F., Carette, R., Elbattah, M., Guérin, J., & Dequen, G. (2022). Eye-tracking dataset to support the research on autism spectrum disorder. In Proceedings of the 1st Workshop on Scarce Data in Artificial Intelligence for Healthcare (59-64). https://doi.org/10.5220/0011540900003523

Conference Name IJCAI–ECAI Workshop on Scarce Data in Artificial Intelligence for Healthcare (SDAIH), 2022
Conference Location Vienna, Austria
Start Date Jul 25, 2022
End Date Jul 25, 2022
Acceptance Date May 17, 2022
Online Publication Date Mar 18, 2023
Publication Date 2022
Deposit Date Mar 19, 2023
Publicly Available Date Mar 20, 2023
Volume 1
Pages 59-64
Book Title Proceedings of the 1st Workshop on Scarce Data in Artificial Intelligence for Healthcare
DOI https://doi.org/10.5220/0011540900003523
Keywords Autism Spectrum Disorder, ASD, Eye-Tracking, Machine Learning
Public URL https://uwe-repository.worktribe.com/output/10570768
Publisher URL https://www.scitepress.org/Link.aspx?doi=10.5220/0011540900003523

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