Artificial Intelligence in Dermatopathology: An Update and Review of the Current Literature

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Abstract
Artificial intelligence (AI) has pervaded many fields of medicine in the last few years on the wave of similar changes in other disciplines. Adoption of AI-driven technologies will progress in pathology in the years to come and will also transform our subspecialty of dermatopathology. From the adoption of AI in teaching to its use in clinical practice and in advancing our field through improved research capabilities, we expect a great deal of changes that will hopefully improve our assessment of tissue sections for several cutaneous pathologies. In this review, we offer an overview of where the use of these tools currently stands in dermatopathology and the potential directions that will transform the way we practice and do research. We cover AI’s role in diagnosing various skin conditions, such as melanocytic lesions and other cutaneous skin cancers, and inflammatory dermatoses. The review further covers AI’s contributions to workflow automation, like mitotic figure detection and counting, predictive analytics (e.g., melanoma prognosis), and educational tools (e.g., AI-driven simulators). It also addresses critical technical aspects, including data curation, algorithm development, and model validation. We aim to provide a comprehensive overview of how AI is transforming dermatopathology, from diagnosis and prognosis to education and clinical integration.

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