TMS: Ensemble Deep Learning Model for Accurate Classification of Monkeypox Lesions Based on Transformer Models with SVM
The results of the study show that the proposed hybrid framework achieves robust diagnostic performance in monkeypox detection, offering potential utility for enhanced disease monitoring and outbreak management. The model's high diagnostic accuracy and computational efficiency indicate that it can be used as an additional tool for clinical decision support.
Authors
- Elsaid Md. Abdelrahim (ORCID: https://orcid.org/0000-0002-5054-3703)
- Radwa Ahmed Osman (ORCID: https://orcid.org/0000-0003-3663-0103)
- Hasan Hashim (ORCID: https://orcid.org/0009-0006-6724-7499)
- El-Sayed Atlam (ORCID: https://orcid.org/0000-0002-4728-590X)
- Ibrahim Gad (ORCID: https://orcid.org/0000-0003-3388-9144)
Institutions
- Northern Border University (SA)
- Tanta University (EG)
- Taibah University (SA)
- Arab Academy for Science, Technology, and Maritime Transport (EG)
Publication Details
- Journal
- Diagnostics
- Published
- 2024-11-23
- DOI
- https://doi.org/10.3390/diagnostics14232638
- Citations
- 13
- Primary Topic
- Poxvirus research and outbreaks
- Type
- article
- Field-Weighted Citation Impact
- 3.82