Lokman Hekim Health Sciences
Article Open Access Volume 6 · Issue 2 · 2026 pp. 272–281

A Bibliometric Analysis of Artificial Intelligence and Simulation Technologies in Dental Education

Hafize Gamze Demirbaş1 ORCID
1 Department of Restorative Dentistry, Faculty of Dentistry, Aydin Adnan Menderes University, Aydın, Türkiye
Published: 2026 DOI: 10.14744/lhhs.2026.32975 Article ID: LHHS-32975
Abstract
Introduction: Artificial intelligence (AI) and simulation technologies are increasingly used in dental education to improve learning safety, standardization, and skill assessment. This study examines their intersection, including AI-integrated simulations and curricula that apply AI and simulation separately. Despite rapid growth, the intellectual structure and trends of this intersection have not been comprehensively delineated in focused studies. We therefore conducted a bibliometric analysis of the literature.
Methods: Publications indexed in the Web of Science Core Collection from 2010 to 2026 were included. The search captured studies addressing dental education, simulation technologies, and AI applications. Bibliometrix in R was used to analyze publication trends, journals, countries, institutions, authors, and keyword patterns. Collaboration networks and keyword co-occurrence were visualized with VOSviewer. Only English-language articles and reviews were included. Results: Publications increased markedly after 2019. Early research centered on virtual reality and simulation-based training, whereas recent studies emphasize AI, machine learning, and automated performance assessment. The United States and China were the most productive countries, with limited international collaboration. Keywords indicate a shift from immersive simulation toward AI-driven, adaptive, and data-informed educational systems. Both AI-integrated simulations and standalone AI or simulation applications were represented, reflecting diverse approaches. Discussion and Conclusion: AI and simulation technologies constitute a growing research domain in dental education. The field is moving from technology-assisted simulation toward AI-enhanced systems, reflecting evolving research priorities rather than established clinical superiority. Future work should use standardized, multicenter, outcome-focused designs to assess educational effectiveness and relevance.

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