Smart Dermatology: Hybrid deep learning and Explainable AI Framework for Early Automated Melanoma Detection of Skin Lesion

Skin cancer is a fatal type of cancer and a leading cause of death worldwide. Many lives can be saved if detected early. The skin is the largest organ in the human body, and skin cancer is one of the most dangerous types of cancer. Various genetic changes can cause abnormal cell growth in the body. These changes in skin cells can be extremely harmful. Skin cancer develops slowly and can spread to other parts of the body. Because skin cancer can be fatal, early detection is crucial. Examining the skin for signs of cancer through sight and touch can be challenging. There are many challenges in the early detection of skin cancer due to multiple simulates on lesions. This paper presents a new, early, automated melanoma detection model based on deep learning for skin lesions. This model is based on a mathematical model to improve detection performance. The experiment is applied to the two recent skin cancer lesion image benchmarks from 2024, which include 18310091 and 14991071 dermoscopic images of lesions and contour images.