Automated Diagnosis of Skin Cancer using Deep Learning: A Multi-Center Study

Abstract

This paper investigates the application of deep learning techniques for automated diagnosis of skin cancer across multiple healthcare centers. By leveraging convolutional neural networks (CNNs) trained on large-scale dermoscopic image datasets, the proposed AI system demonstrates high accuracy in classifying skin lesions into benign and malignant categories. The study highlights the potential of AI-powered diagnostic tools to assist dermatologists in early detection and treatment decision-making, ultimately improving patient care and reducing healthcare costs.