Digital Intelligence in Dental Education: A Bibliometric Analysis

Background: Recent years have witnessed a surge in the integration of digital intelligence within dental education, with various technologies increasingly supporting clinical skill training and educational applications. This study aims to map the knowledge landscape of digital intelligence applications in dental education through a bibliometric analysis. Methods: A comprehensive literature search was conducted in the Web of Science Core Collection to identify relevant publications on digital intelligence in dental education. Bibliometric parameters were analysed qualitatively and quantitatively using Microsoft Excel 2019, Incites and CiteSpace software. Results: Of 606 initially retrieved publications, 424 were included in the analysis. Annual publication output remained relatively low from 2000 to 2020, followed by a pronounced increase in 2024 and 2025. Among the ten most-cited articles, the top seven were review articles. The most productive countries were the USA (n = 47, 12%), China (n = 40, 10%), and England (n = 28, 7%). The most active journals were the Journal of Dental Education, European Journal of Dental Education, and BMC Medical Education. Trend analysis via CiteSpace revealed an evolution in research focus from computer simulation (2010) to learning environments (2019) and, more recently, artificial intelligence (2024). Keyword clustering identified five thematic groups: artificial intelligence, computer-assisted instruction, skill assessment, haptic simulation, and simulation. Conclusions: This study offers insights and guidance for researchers interested in digital intelligence applications in dental education. With the rapid advancement of digital intelligence, dental education is poised to benefit substantially. Educators should strategically integrate digital tools and pedagogical concepts to enhance teaching methods and adapt to future educational demands.