Skin Cancer Detection Using Different Deep Learning Models

This study investigates the application of deep learning models, including CNN, ResNet50, and VGG16, for the early detection of skin cancer. Utilizing a dataset of 3,307 images, the models were trained to classify skin lesions as benign or malignant. The results demonstrate promising performance, with ResNet50 and VGG16 achieving high training accuracies of 99.60% and 97.58%, respectively. These findings highlight the potential of deep learning in assisting dermatologists in the early detection and diagnosis of skin cancer, leading to improved patient outcomes.