Classification of Skin Cancer via Deep Learning and Transfer Learning
Non-melanoma skin cancer is the most common type of cancer diagnosed in humans. Although the procedure of skin carcinogenesis is unclear, a number of reports have been carried out to exceptionally explain the contrivances that lead to malignancy; (2) Methods: We reviewed the literature regarding the pathogenesis of benign skin cancer, with a focus on basal cell carcinomas, squamous cell carcinomas, and actinic keratosis; (3) Results: Several studies reported genetic and molecular alterations that result in non-melanoma skin cancer. Numerous risk factors, such as genetic and molecular alterations, immune suppression, and UV radiation, are involved in the pathogenesis of non-melanoma skin cancer. (4) Conclusion: Despite the fact that skin carcinogenesis is still unclear, several papers showed that genetic and molecular alterations are involved in this process. Furthermore, a number of risk factors for non-melanoma skin cancer are now understood, making it possible to effectively prevent the development of non-melanoma skin cancer. Our evaluation concentrated on molecular and genetic components and conducted a detailed analysis in contrast to other articles on the same subject. Non-melanoma skin cancer is caused by a number of reasons. Four performance metrics have been calculated to compare the suggested approach with the current approaches, and the findings show that the suggested approach performed better. The obtained accuracy, precision, recall, and F score rates are 95.5%, 95.4%, 95.5%, and 95.4%, respectively.
Authors
- Deena Nath Gupta (ORCID: https://orcid.org/0000-0001-6323-411X)
- Khushmeen Kaur Brar
Institutions
- Chandigarh University (IN)
- Centre for Development of Advanced Computing (IN)
Publication Details
- Published
- 2025-03-21
- DOI
- https://doi.org/10.1109/comp-sif65618.2025.10969900
- Citations
- 1
- Primary Topic
- Cutaneous Melanoma Detection and Management
- Type
- article
- Field-Weighted Citation Impact
- 1.05