Accuracy of artificial intelligence in implant dentistry: A scoping review with systematic evidence mapping.

ABSTRACT

STATEMENT OF PROBLEM: The use of artificial intelligence (AI) in dentistry has grown. However, the accuracy of clinical applications in implant dentistry is still unclear. PURPOSE: The purpose of this scoping review with systematic evidence mapping was to identify and describe the available evidence on the accuracy and clinical applications of AI in implant dentistry. MATERIAL AND METHODS: An electronic search was performed in 4 databases and nonpeer-reviewed literature for articles published up to November 2023. The eligibility criteria comprised observational and interventional studies correlating AI and implant dentistry. A bibliographic mapping and quality analysis of the included studies was conducted. Additionally, the accuracy rates of each AI model were evaluated. RESULTS: Twenty-six studies met the inclusion criteria. A significant increase in evidence has been observed in recent years. The most commonly found applications of AI in implant dentistry were for the recognition of implant systems followed by surgical implant planning. The performance of AI models was generally high (mean of 88.7%), with marginal bone loss (MBL) prediction models being the most accurate (mean of 93%). Regarding the place of publication, the Asian continent represented the highest number of studies, followed by the European and South American continents. CONCLUSIONS: Evidence involving AI and implant dentistry has grown in the last decade. Although still under development, all AI models evaluated demonstrated high accuracy and clinical applicability. Further studies evaluating the clinical efficacy of AI models in implant dentistry are essential.