A Comprehensive Study of Different Skin Cancer Detection Models Using Deep Learning Techniques

Abstract

Skin cancer is a highly prevalent disease that exhibits rapid growth worldwide. The timely identification and accurate diagnosis of skin cancer are of paramount importance in the context of preventive measures. The identification of skin cancer in its early stages poses a significant challenge for dermatologists. In recent years, machine learning techniques have been widely employed in both supervised and unsupervised learning tasks to address this issue. In this study, different existing techniques to detect different types of skin cancers and the evaluation metrics to assess their performance are dealt with.