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Artificial Intelligence for the Oral and Maxillofacial Surgeon
John M Nathan1, Jay Shim2, Kevin Arce3
1Senior Associate Consultant, Division of Oral and Maxillofacial Surgery, Department of Surgery, Mayo Clinic, Rochester, MN.
Background:
Artificial intelligence (AI) and machine learning (ML) (AI/ML) has grown exponentially over the past several years. However, oral and maxillofacial surgeons have limited education and exposure to AI in the clinical and administrative setting. The purpose of this review is to provide an introduction of core concepts in commonly used AI models while providing relevant context in oral and maxillofacial surgery (OMS). Challenges and potential solutions to development of AI in OMS are also discussed.
Findings:
Preliminary studies using AI/ML in OMS have demonstrated high performance in metrics including sensitivity, specificity, Dice coefficient, intersection over union, and residual error.
Conclusions And Relevance:
Oral and maxillofacial surgeons should have a functional knowledge of AI technologies to guide development, testing, and adoption into OMS. With surgeon guidance, AI/ML has the potential for meaningful application across multiple clinical and administrative domains of OMS.
