A bibliometric analysis of the literature from the past to the present on the use of artificial intelligence in orthodontics and orthognathic surgery

Authors : İbrahim Tevfik Gülşen, Ruşen Erdem, Yavuz Selim Genç, Emine Gülşen
Pages : 395-404
Doi:10.32322/jhsm.1650514
View : 112 | Download : 90
Publication Date : 2025-05-30
Article Type : Research Paper
Abstract :Aims: This study aims to investigate the publication characteristics of academic work centred around artificial intelligence (AI) in orthodontics and orthognathic surgery in detail. Methods: In this analysis, the VOSviewer software and the Bibliometrix Biblioshiny R-package were employed for the purposes of bibliometric investigation and data visualisation. Results: Between 1991 and 2024, 842 articles were published, averaging 12.33 citations per article. China topped the list with 200 articles, succeeded by the U.S. with 183 and South Korea with 121. Seoul National University authored the highest number of publications (47), succeeded by Peking University (36) and the University of North Carolina (34). Seoul National University (807) and the Catholic University of Leuven (567) ranked highest in citation impact. Jacobs Reinhilde was the most prolific author, with 22 publications, and alongside Dinggang Shen and Adriaan Van Gerven, had the greatest citation counts of 544, 491, and 476, respectively. The most used keywords were “artificial intelligence,” “deep learning,” “machine learning,” “orthodontics,” “convolutional neural network,” “orthognathic surgery,” “dentistry,” “cephalometry,” “CBCT,” and “cephalometric analysis.” Conclusion: This bibliometric analysis illustrates that AI has swiftly become an expanding research subject in orthodontics and orthognathic surgery, attracting considerable interest from the scientific community. The thorough investigation indicates that AI is essential, especially in cephalometric evaluations, diagnostic procedures, and treatment strategies.
Keywords : Yapay zeka, Bibliyometrik analiz, Ortodonti, Ortognatik cerrahi

ORIGINAL ARTICLE URL