Practical considerations for adopting artificial intelligence clinical decision support tools and large language...

Artificial intelligence (AI) in dermatology is a rapidly evolving field, offering promising advances in the diagnosis and management of skin cancers. As global skin cancer incidence rises, tools such as machine learning-based systems and large language models have shown significant potential to support triage of patients with skin cancer. Yet, several key practical and ethical considerations stand in the way of widespread adoption. Limitations in dataset diversity, medicolegal ambiguity, and concerns regarding transparency of AI-generated outputs are challenges that must be addressed. This review explores the current landscape of AI technologies in dermatology, including diagnostic imaging tools, workflow-integrated systems, and generative AI models. We evaluate the advantages and limitations of these tools, workflow optimization, patient trust in AI-driven preliminary diagnoses, and the importance of preserving the physician-patient relationship amid increasing AI integration in dermatology.