The Use of Resnet50 for Skin Cancer Analysis

Skin cancer remains a critical global health concern, with over 2.1 million cases diagnosed annually, many in areas with limited access to dermatological care. Providing an accurate diagnosis on time is essential but challenging in rural and backward areas. The growth of artificial intelligence (AI) and deep learning has shown significant potential in aiding skin cancer detection and classification. This study focuses on using deep learning models like CNN for categorization of skin lesions. This review discusses different CNN architectures and methodologies, emphasizing the need for further innovation to enhance model accuracy across multiple classes, thus supporting widespread, accessible diagnostic solutions.