Background and Aim: To provide the first bibliometric analysisfocused exclusively on artificial intelligence (AI) in periodontology,mapping publication trends, contributors, collaboration networks,and thematic hotspots.Materials and Methods: The Web of Science Core Collectionwas searched on May 8, 2025 using AI- and periodontologyrelatedterms. Only original research articles were included.Bibliographic data from 206 eligible records were analyzed inVOSviewer (v1.6.20) to generate networks of co-authorship,keyword co-occurrence, country- and institution-levelcollaboration, citation patterns, and source journals; minimumthresholds were applied for robust clustering.Results: Relevant literature began in 2005, with a sharp riseafter 2018 and a peak in 2024. The United States and Chinawere the most productive countries, and Türkiye ranked third.In the co-authorship network, Kaan Orhan occupied the mostcentral position. Dominant keywords were “periodontitis,”“machine learning,” and “deep learning,” indicating an emphasison diagnostic/classification tasks. Temporal overlays showed ashift from early algorithm development toward clinically orienteddiagnostic and decision-support applications. Citation mappingsuggested that earlier influential papers were often isolated,whereas recent studies were more integrated. The Journal ofDentistry was the most productive and well-connected source.Conclusion: AI research in periodontology is expanding rapidlywith increasing clinical orientation. Strengthening internationalcollaboration and extending work beyond diagnosis totherapeutic and prognostic applications could enhance clinicalimpact and global integration.
Muluk et al. (Mon,) studied this question.
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