Application of artificial intelligence in the design of single tooth-supported restorations: A systematic review.

STATEMENT OF PROBLEM: Designing dental prostheses using computer-aided design software programs can be complex and time-consuming. To address this challenge, artificial intelligence (AI) has been increasingly integrated into the design process. While many studies have evaluated the impact of AI-based applications on dental restoration design, a systematic overview of these findings is lacking. PURPOSE: The purpose of this systematic review was to evaluate the design of single tooth-supported restorations using AI-based software programs. MATERIAL AND METHODS: A comprehensive literature search was conducted across 4 databases followed by a manual search. Studies investigating factors related to the performance of AI-based design of single tooth-supported restorations were included. The studies were evaluated by 2 independent reviewers, using the Joanna Briggs Institute critical appraisal. In cases of disagreement, a third reviewer was consulted to reach a consensus. RESULTS: After reviewing the full-text articles, 22 studies were included in the analysis. The articles were classified according to 3 identified parameters related to the performance of AI-based designed restorations: Restoration design, time efficiency and biomechanical properties. The restoration design parameter was further analyzed across 7 subcategories: detection of tooth finishing line, marginal fit, internal adaptation, interproximal contacts, occlusion, and esthetic integration. CONCLUSIONS: The findings of this review suggest that AI-based design of single tooth-supported restorations holds substantial potential for improving efficiency, internal fit, esthetic integration, and occlusal morphology compared to manual design methods. While the initial results were promising, they were based solely on in vitro investigations; therefore, further clinical validation is required to fully establish the reliability and clinical applicability of AI-generated crowns in routine dental practice.