Artificial intelligence in dermatology: The shifting paradigms

Artificial intelligence (AI) is revolutionizing dermatological practice, fundamentally transforming diagnostic methodologies, treatment approaches, and patient care delivery systems. This perspective examines the current landscape of AI integration in dermatology, with particular emphasis on the Indian healthcare context. The rapid advancement of deep learning algorithms, particularly convolutional neural networks (CNNs), has achieved diagnostic accuracies comparable to board-certified dermatologists in skin cancer detection, with sensitivities reaching 87% and specificities of 77% across various conditions. Current applications demonstrate significant promise in conditions ranging from melanoma detection to inflammatory dermatoses, with AI-powered tools showing superior performance in lesion counting and severity assessment compared to manual evaluation. However, challenges persist, including dataset bias, particularly underrepresentation of darker skin tones, regulatory uncertainties, and the need for comprehensive training programs. Looking forward, the roadmap for AI in Indian dermatology requires strategic curriculum reform, incorporating AI literacy into residency training, development of culturally diverse datasets, and establishment of robust validation frameworks. The rise of vision-language models combined with collaborative learning presents a unique chance to make dermatological knowledge more accessible, especially in areas with limited resources. This transformation demands adaptive strategies from practicing dermatologists, emphasizing continuous learning, ethical AI implementation, and collaborative approaches to technology integration. The future of dermatology lies in augmented intelligence, where AI serves as a powerful ally rather than a replacement, enhancing diagnostic precision and expanding access to specialized care across India's diverse healthcare landscape.