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

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

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.

• Presentation Conference Type: Conference Paper (published)
• Conference Name: IJCAI–ECAI Workshop on Scarce Data in Artificial Intelligence for Healthcare (SDAIH), 2022
• 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