Artificial Intelligence In Dentistry: A Bibliometric Analysis

To conduct a bibliometric analysis of machine learning applications in stomatology from 2005 - 2024, identify research hotspots and frontiers Retrieved 2,640 articles from Web of Science Core Collection. Analyzed data using Citespace, VOSviewer, R package bibliometrix, Excel, and Scimago Graphica. Publication volume increased since 2018, with a spike in 2020. China led in publications, while the US had high cooperation intensity and paper quality. Disease diagnosis, especially for oral cancer and periodontal diseases, was the main application. CNN and SVM were the most used algorithms. Machine learning in stomatology has attracted growing attention. Future research may focus on new neural network architectures, bone loss - related diseases, orthodontics, population - based oral health analysis, and surgical robotics. However, the study has limitations in literature retrieval scope.