Skin Cancer Detection with Deep Learning

Abstract

Skin cancer is a serious public health concern, and early detection is essential for effective treatment. This research explores the use of Deep Learning, particularly Convolutional Neural Networks (CNNs), in the automatic classification of skin lesions from medical images. The study includes an introduction to deep learning in medicine, a detailed explanation of CNN architecture, and a practical implementation using the Melanoma Cancer Image Dataset from Kaggle. Results show that CNNs can achieve high accuracy in detecting melanoma, making them promising tools for clinical support. Challenges such as data imbalance and variability in skin tone are also discussed.