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Dermatology is currently seeing a substantial transformation due to the integration of Artificial Intelligence, particularly through the use of machine learning and convolutional neural networks. AI’s potential in dermatology is based on its ability to increase visual diagnosis, which is a core aspect of dermatological practice. This integration promises improvements in diagnostic precision, process efficiency, and personalized patient care. Although there has been some progress, there are still obstacles that need to be overcome. The ethical considerations surrounding the confidentiality of medical data, and the transparency of AI algorithms, are of utmost importance. Additionally, the availability of high-quality, annotated dermatological datasets is a limiting factor, alongside with the need for substantial technical investments and training for healthcare professionals. This article provides an extensive analysis of AI's impact on dermatology, presenting its applications in various domains and discussing the associated challenges. By highlighting AI’s potential and addressing its challenges, the article aims to contribute to a deeper understanding of how AI can enhance dermatological practices to achieve better patient outcomes.
Manole et al. (Thu,) studied this question.