Şehrazat Ziya Muluk, Murtaza Yelbay, Merter Güçlü
Clinical Dentistry and Research - 2026;50(1):12-22
Background and Aim: To provide a bibliometric analysis focused exclusively on artificial intelligence (AI) in periodontology, mapping publication trends, contributors, collaboration networks, and thematic hotspots. Materials and Methods: The Web of Science Core Collection was searched on May 8, 2025 using AI- and periodontology-related terms. Only original research articles were included. Bibliographic data from 206 eligible records were analyzed in VOSviewer (v1.6.20) to generate networks of co-authorship, keyword co-occurrence, country- and institution-level collaboration, citation patterns, and source journals. Minimum thresholds were applied for robust clustering. Results: Relevant literature began in 2005, with a sharp rise after 2018 and a peak in 2024. The United States and China were the most productive countries, and Türkiye ranked third. In the co-authorship network, Kaan Orhan occupied the most central position. Dominant keywords were "periodontitis," "machine learning," and "deep learning," indicating an emphasis on diagnostic/classification tasks. Temporal overlays showed a shift from early algorithm development toward clinically oriented diagnostic and decision-support applications. Citation mapping suggested that earlier influential papers were often isolated, whereas recent studies were more integrated. The Journal of Dentistry was the most productive and well-connected source. Conclusion: AI research in periodontology is expanding rapidly with increasing clinical orientation. Strengthening international collaboration and extending work beyond diagnosis to therapeutic and prognostic applications could enhance clinical impact and global integration.
