Multimodal skin lesion classification for early cancer diagnosis using deep learning
Combining DenseNet-201, InceptionV3, and VGG16, the proposed ensemble model outperforms the individual models with a testing accuracy of 97.9%. Additionally, it exhibits a better F1-score, recall, and precision of 99.2%, demonstrating its efficacy in automated skin lesion detection.
Authors
- K Shyamala
- Vandit Gabani
- Vinita Kishore Vaswani Rajpal
- T. M. Navamani
Institutions
- Vellore Institute of Technology University (IN)
Publication Details
- Journal
- Frontiers in Physiology
- Published
- 2026-02-09
- DOI
- https://doi.org/10.3389/fphys.2026.1717517
- Primary Topic
- Cutaneous Melanoma Detection and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00