Novel deep learning for multi-class classification of Alzheimer’s in disability using MRI datasets
We hope that our proposed framework may automate the precise classifications of various AD categories, and thereby can offer the prompt management and treatment of cognitive and functional impairments associated with AD.
Authors
- A. S. Al-Moisheer (ORCID: https://orcid.org/0000-0002-2764-686X)
- Naif Alotaibi (ORCID: https://orcid.org/0000-0002-6789-3363)
- Mohammad Ali Moni (ORCID: https://orcid.org/0000-0003-0756-1006)
- Touhid Bhuiyan (ORCID: https://orcid.org/0000-0002-6747-0846)
- AKM Azad (ORCID: https://orcid.org/0000-0002-5251-2214)
- Salem A. Alyami (ORCID: https://orcid.org/0000-0002-5507-9399)
- Mohammad Yousuf (ORCID: https://orcid.org/0000-0003-0101-4749)
- Md. Hasanul Kabir (ORCID: https://orcid.org/0000-0002-6853-8785)
- Simra Shahid (ORCID: https://orcid.org/0009-0009-6981-9923)
- Maleeha Kaikaus
Institutions
- Charles Sturt University (AU)
- University of Washington (US)
- Imam Mohammad ibn Saud Islamic University (SA)
- Jahangirnagar University (BD)
Publication Details
- Journal
- Frontiers in Bioinformatics
- Published
- 2025-08-20
- DOI
- https://doi.org/10.3389/fbinf.2025.1567219
- Citations
- 3
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 4.41
Funders
- King Salman Center for Disability Research