Veena Dillshad1, Muhammad Attique Khan2,*, Muhammad Nazir1, Jawad Ahmad2, Dina Abdulaziz AlHammadi3, Taha Houda2, Hee-Chan Cho4, Byoungchol Chang5,*
CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5299-5321, 2025, DOI:10.32604/cmc.2025.063851
- 19 May 2025
Abstract Globally, skin cancer is a prevalent form of malignancy, and its early and accurate diagnosis is critical for patient survival. Clinical evaluation of skin lesions is essential, but several challenges, such as long waiting times and subjective interpretations, make this task difficult. The recent advancement of deep learning in healthcare has shown much success in diagnosing and classifying skin cancer and has assisted dermatologists in clinics. Deep learning improves the speed and precision of skin cancer diagnosis, leading to earlier prediction and treatment. In this work, we proposed a novel deep architecture for skin cancer… More >