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Generative artificial intelligence in dentistry: a bibliometric analysis

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  • Zambrano-Olvera, Cristina Valeria
  • Perez-Rizzo, Rosaria

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.

Suggested Citation

  • Zambrano-Olvera, Cristina Valeria & Perez-Rizzo, Rosaria, 2026. "Generative artificial intelligence in dentistry: a bibliometric analysis," SAP Artificial Intelligence in Dentistry, South American Publishing.
    • Handle: RePEc:cwf:aidart:aid202690
    DOI: 10.62486/aid202690
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