Diagnosing autism spectrum disorders using a double deep Q-Network framework based on social media footprints
Ultimately, the proposed system was compared against the existing system that used the same dataset. The proposed approach is based on variations in the text of social media interactions, which can assist physicians and clinicians in performing symptom studies within digital footprint environments.
Authors
- Ahmed Abdullah Alqarni (ORCID: https://orcid.org/0000-0002-6628-9797)
- Nesren Farhah (ORCID: https://orcid.org/0000-0002-2103-1282)
- Sultan Ahmad (ORCID: https://orcid.org/0000-0002-3198-7974)
- Nadhem Ebrahim (ORCID: https://orcid.org/0000-0001-9975-589X)
Institutions
- University of Akron (US)
- Lovely Professional University (IN)
- Saudi Electronic University (SA)
- Prince Sattam Bin Abdulaziz University (SA)
- King Salman Center for Disability Research (SA)
- Al Baha University (SA)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2025-08-20
- DOI
- https://doi.org/10.3389/fmed.2025.1646249
- Citations
- 1
- Primary Topic
- Autism Spectrum Disorder Research
- Type
- article
- Field-Weighted Citation Impact
- 1.43
Funders
- King Salman Center for Disability Research