Generative artificial intelligence in dentistry: a bibliometric analysis

Cristina Valeria Zambrano-Olvera and Rosaria Perez-Rizzo

SAP Artificial Intelligence in Dentistry, 2026

Abstract: Introduction: Large language models and generative artificial intelligence have spread rapidly through dentistry, but the volume and structure of the corresponding literature have not been mapped. Methods: A bibliometric analysis of the Scopus-indexed literature was performed. Results: The query retrieved 1,777 documents published between 2022 and 2026 across 720 sources and 93 countries. Annual production grew from 1 document in 2022 to 900 in 2026 (an annual growth rate of 447.7%), and the corpus accumulated 15,608 citations (mean 8.8; h-index 54), with 42.8% of documents uncited. Conclusions: The field emerged in 2022, grew exponentially thereafter, and was led by Turkey, the United States, and China, with concentration in oral-health and dental-education journals.

Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:cwf:aidart:aid202690

DOI: 10.62486/aid202690

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