Artificial Intelligence in the Management of Diabetic Patients in Dental Practice: From Risk Assessment to Personalized Treatment
Author(s):
Alireza.R.Azadi and Omid Panahi
The global epidemic of diabetes mellitus presents significant challenges for dental practitioners, who must navigate the complex oral manifestations of this systemic disease while contributing to overall patient health. Artificial intelligence technologies offer transformative potential for enhancing every aspect of dental care for diabetic patients, from initial risk assessment through treatment planning and long-term maintenance. This comprehensive review examines the current landscape of AI applications specifically tailored to managing diabetic patients in dental settings. We explore AI-powered diagnostic tools for identifying diabetes-related oral complications, machine learning algorithms for predicting treatment outcomes, and intelligent systems for optimizing periodontal therapy in patients with dysregulated glucose metabolism. The review synthesizes evidence from clinical studies evaluating AI applications including convolutional neural networks for radiographic assessment of diabetes-related bone changes, natural language processing for extracting diabetes status from dental records, and predictive models for implant survival in diabetic patients. We address the unique considerations for treating diabetic patients, including medication interactions, wound healing complications, and infection risk, and examine how AI decision support can mitigate these challenges. Implementation barriers including algorithm transparency, clinician training requirements, and integration with existing practice management software are critically evaluated. Finally, we propose a comprehensive framework for AI-enhanced dental care of diabetic patients that spans the continuum from prevention through complex rehabilitation.