Advances in Skin Cancer Detection: CNNs and Deep Learning Strategies

The common and dangerous condition skin cancer calls early discovery for efficient treatment. Often time-consuming, manual diagnosis by dermatologists might cause delays in diagnosis and treatment. CNN s provide a strong answer to handle this difficulty. CNNs are excellent in learning complex patterns suggestive of malignant lesions, hence improving diagnosis speed and accuracy. This automated system helps doctors in crucial circumstances as well as help to lower healthcare expenditures. This work presents a CNN-based approach with 91% accuracy for skin cancer screening. Complementing Sustainable Development Goals (SDGs) related to health, innovation, technology, and affordable health care, the study shows the effectiveness of deep learning in separating benign from malignant skin lesions, so acting as a useful tool for early detection and diagnosis.