Skin Cancer Detection Using Deep Learning

Skin cancer remains a major global health concern, demanding accurate and timely diagnosis. This study explores multiple machine learning techniques—SVM, Decision Trees, Random Forest, MLP, and ensemble methods—for classifying skin lesions, with a primary focus on the Cascaded Convolutional Neural Network (CNN) model. A diverse, pre-processed dataset enhances model performance and generalization. The Cascaded CNN proves highly effective and is integrated into a Flask-based web application, allowing users to upload lesion images for real-time predictions. The findings highlight the model’s potential in supporting early diagnosis and treatment planning.