The Position of Artificial Intelligence in Academic Dentistry?

Abstract

This study aims to conduct a bibliometric analysis research to evaluate the interaction between dentistry and artificial intelligence as reflected in academic publications. Publications on artificial intelligence in dentistry were retrieved from the Web of Science Core Collection database. Covariates included publication count, citation count, year range, centrality value, and silhouette value. Bibliometric analysis was conducted using CiteSpace, VOSviewer, and R-Studio software. There were a total of 2.510 publications constituting the literature from 2000 to 2024. The publication count shows a growth rate of 5.87% over time.The University of Michigan was the institute with the highest publication and collaboration count. The Journal of Dental Research led in publications with 145 articles, followed by BMC Oral Health with 105 articles and the Journal of Dentistry with 89 articles. Additionally, there were 11 core journals forming Bradford's Law Scatter, with Lee et al.'s publication from 2018 having the highest citation count of 333 and 115 co-citations. In the analysis of keyword citation burst, the term 'amelogenesis imperfecta' was the most bursty keyword with a burst strength of 22.11 from 2000 to 2016. The only keyword that continued its citation burst today was 'deep learning', which started its citation burst in 2022. The results obtained in this study highlight the characteristic features of artificial intelligence applications in dentistry. With artificial intelligence being a relatively young field, similar bibliometric analysis studies in the future can track the developmental journey of the literature and make predictions about its future.

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