Leveraging Convolution Neural Network (CNN) for Skin Cancer Identification

Skin cancer is one of the most prevalent types of cancer globally, with melanoma being the most aggressive form.Early detection greatly enhances the prognosis and results of treatment.With advancements in deep learning, Convolutional Neural Networks (CNNs) have demonstrated remarkable performance in various image classification tasks, including medical image analysis.This paper reviews recent research efforts in leveraging CNNs for skin cancer identification.We discuss the challenges associated with skin cancer detection, highlight the architecture and training strategies of CNN models, and present a comprehensive overview of existing datasets and evaluation metrics.Furthermore, we analyze the strengths and limitations of CNN-based approaches, identify emerging trends, and propose potential avenues for future research in this critical domain.