Practical Considerations for Adopting AI Clinical Decision Support Tools and Large Language Models in Dermatology.
Dhamsania IR, Zhou AE, Khalilzadeh DM, Vidal NY, Ferris LK, Grant-Kels JM
Clinics in DermatologyIn the feed 21 Sep 2026, published online 21 Sep 2026, issue 2026 Sep 21, added to PubMed 21 Sep 2026
Topics: Skin cancer & tumorsImaging, dermoscopy & AIPractice, education & research
Abstract
Artificial Intelligence (AI) in dermatology is a rapidly evolving field, offering promising advancements in the diagnosis and management of skin cancers. As global skin cancer incidence rises, tools like machine-learning based systems and large language models (LLMs) have demonstrated significant potential in supporting triage of skin cancer patients. 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 with increasing integration of AI in dermatology.
Abstract from PubMed
PMID 42767470 · DOI 10.1016/j.clindermatol.2026.09.012