Diagnosing autism spectrum disorder based on eye tracking technology using deep learning models
The system successfully diagnosed ASD using the ET dataset. This approach shows promise for clinical application, assisting healthcare professionals in diagnosing ASD more accurately through advanced artificial intelligence technology.
Authors
- Mosleh Hmoud Al-Adhaileh (ORCID: https://orcid.org/0000-0002-3519-1121)
- Abdullah H. Al-Nefaie (ORCID: https://orcid.org/0000-0002-3344-2302)
- Ayoub K. Al-Hamadi (ORCID: https://orcid.org/0000-0002-3632-2402)
- Sultan Ahmad (ORCID: https://orcid.org/0000-0002-3198-7974)
- Saleh Nagi Alsubari (ORCID: https://orcid.org/0000-0002-9793-2888)
Institutions
- Lovely Professional University (IN)
- Saudi Electronic University (SA)
- Prince Sattam Bin Abdulaziz University (SA)
- Riyadh Elm University (SA)
- King Salman Center for Disability Research (SA)
- King Faisal University (SA)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2025-10-09
- DOI
- https://doi.org/10.3389/fmed.2025.1690177
- Primary Topic
- Autism Spectrum Disorder Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- King Salman Center for Disability Research