DIGITAL TRANSFORMATION IN DERMATOLOGY: THE ROLE OF ARTIFICIAL INTELLIGENCE IN THE EARLY DIAGNOSIS OF SKIN CANCER

Abstract

Artificial Intelligence (AI) has emerged as an important tool to support the diagnosis and screening of dermatological diseases, particularly skin cancer. This study aimed to analyze recent scientific evidence regarding the application of AI in dermatology, with emphasis on the early detection, classification, and prognosis of skin lesions. A literature review was conducted using scientific articles published between 2024 and 2026, retrieved from the CAPES Periodicals Portal and PubMed databases. The findings demonstrated that deep learning algorithms, convolutional neural networks, and multimodal AI systems achieve high accuracy in identifying skin lesions, supporting the early diagnosis of melanoma, basal cell carcinoma, and other skin cancers. Furthermore, the integration of AI with teledermatology tools has shown potential to expand access to specialized healthcare services, particularly in regions with a shortage of dermatologists. However, challenges related to database quality, representation of different skin phototypes, algorithmic bias, data privacy, and regulatory issues still limit large-scale implementation. It is concluded that Artificial Intelligence represents a promising technology for supporting clinical decision-making and improving dermatological diagnosis, contributing to early detection and better clinical outcomes for patients.