Automated Detection and Classification of Skin Lesions using Deep Learning for Early Skin Cancer Diagnosis

Abstract

This study presents an automated approach for the detection and classification of skin lesions using deep learning techniques to facilitate early diagnosis of skin cancer. By analyzing dermatoscopic images and patient clinical data, our deep learning model accurately identifies malignant and benign skin lesions, enabling timely intervention and treatment. Integration of this approach into clinical practice enhances dermatologists' diagnostic accuracy, reduces unnecessary biopsies, and improves patient outcomes in skin cancer management.