This systematic review and meta-analysis comprehensively evaluated all published studies on artificial intelligence (AI) applications in Mohs micrographic surgery and dermatologic surgery. The analysis assessed AI performance in tumor detection, margin assessment, and surgical planning assistance. Results showed promising accuracy metrics for AI-assisted pathology interpretation, though most studies were limited by small sample sizes and single-center designs. The review identifies current capabilities and gaps in AI integration into dermatologic surgery workflows.

AI demonstrates high accuracy for BCC and SCC detection on frozen sections, but most studies are single-center with limited external validation.

Current AI tools show greatest promise as decision-support aids rather than autonomous diagnostic systems in Mohs surgery.

Integration of AI into Mohs workflow requires addressing scanning speed, regulatory approval, and prospective validation challenges.