Barcelona, 2-3/05/2024.
Dr. Josep Malvehy, from the Dermatology Department at Hospital Clínic de Barcelona, delivered a comprehensive lecture on the integration of artificial intelligence (AI) in dermoscopy during the Curso de Dermatoscopia held in Barcelona.
His presentation focused on the significant role that AI plays in enhancing diagnostic accuracy for skin lesions, especially in the early detection of melanoma.
The course began with an introduction to the expanding applications of AI in dermatology, emphasizing its utility in disease classification through clinical and dermoscopy images. Dr. Malvehy elaborated on the importance of AI in automating the analysis of these images, which helps dermatologists differentiate between benign and malignant lesions with increased precision. He highlighted that AI's capabilities are not limited to tumor pathologies but extend to inflammatory skin conditions, trichology, and nail diseases as well.
In his lecture, Dr. Malvehy explained how machine learning, particularly supervised learning, is applied in dermatological practice. AI models trained on extensive datasets can recognize patterns and classify lesions based on dermoscopic images, providing critical support in clinical decision-making. He also discussed the advancements in convolutional neural networks (CNNs), which have revolutionized the ability to analyze complex medical images in a detailed and efficient manner.
However, the presentation also addressed the challenges and risks associated with AI in healthcare. Dr. Malvehy discussed potential issues such as the risk of AI errors, biases in algorithms, and the perpetuation of existing inequities in healthcare. He stressed the importance of transparency, privacy, and security in the development and use of AI tools, as well as the need for continuous learning and adaptation by healthcare professionals.
The iToBoS project, which aims to create a holistic AI-driven tool for the early detection of melanoma, was presented as an example of how AI can integrate various types of data, including clinical and genomic information, to personalize diagnostic approaches. This project underscores the collaborative nature of AI development, requiring input from dermatologists, computer scientists, and engineers to create reliable and widely applicable diagnostic systems.
Dr. Malvehy concluded his lecture by reflecting on the future of AI in dermatology, expressing confidence in its potential to improve diagnostic workflows and patient outcomes. He called for ongoing research and ethical consideration to ensure that AI tools are implemented responsibly in clinical practice. By the end of the session, participants had a deeper understanding of both the practical applications and the ethical considerations of using AI in dermoscopy and dermatology as a whole.
Find out more at Curso de dermatoscopia, inflamoscopia y tricoscopia (camfic.cat).