AI optimization of complete denture design using facial muscle dynamics.

Abstract

Complete denture therapy remains a fundamental treatment for edentulous patients, yet achieving optimal retention, stability, comfort, and facial esthetics continues to present clinical challenges due to individual variations in oral anatomy and neuromuscular function. Recent advances in artificial intelligence (AI) and digital dentistry have created new opportunities to improve denture design through the analysis of facial muscle dynamics. By integrating three-dimensional facial scanning, digital impression techniques, jaw motion tracking, and machine learning algorithms, AI can evaluate dynamic facial expressions and masticatory movements to generate personalized denture designs that better adapt to each patient’s functional characteristics. AI-driven predictive models facilitate optimization of tooth arrangement, occlusal relationships, flange contours, and border extensions, thereby enhancing prosthesis stability and minimizing the need for repeated clinical adjustments. The incorporation of computer-aided design and computer-aided manufacturing technologies further supports accurate fabrication and efficient clinical workflows. Although challenges such as data standardization, algorithm validation, equipment costs, and clinical integration remain, AI-assisted denture design demonstrates considerable potential to improve treatment outcomes and patient satisfaction. Continued research and interdisciplinary collaboration are expected to refine predictive modeling techniques and establish intelligent, patient-centered prosthodontic solutions that combine functional efficiency, esthetic excellence, and long-term clinical success in complete denture rehabilitation.