ReviewThe Saudi dental journal2026
Artificial intelligence in periodontal disease research: a bibliometric and visualized analysis of global research trends (2007-2025).
Review in The Saudi dental journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- The application of artificial intelligence in systemic lupus erythematosus: a bibliometric analysis of current trends and future directions.Frontiers in medicine · 2026Pooled it
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Periodontal disease is one of the most common diseases in stomatology. With the continuous development of artificial intelligence (AI), its integration with periodontology is rapidly evolving. However, a comprehensive bibliometric analysis mapping this interdisciplinary field is currently lacking. We conducted a bibliometric analysis by retrieving publications related to AI and periodontal disease from the Web of Science Core Collection (WoSCC) for the period January 2007 to July 2025. Data processing and visualization were performed using R (Bibliometrix), VOSviewer, and CiteSpace. A total of 496 relevant articles (437 research papers; 59 reviews) were included. Annual publication output has shown sustained growth, particularly since 2021. China contributed the most publications (153 articles), followed by the United States. Among institutions, Pusan National University, South Korea (32 articles), and Saveetha Institute of Medical and Technical Science, India (31 articles) were the most productive. BMC Oral Health published the highest number of articles (n = 23). The co-authorship network involved 2,604 authors, with Pradeep Kumar Yadalam being the most prolific (15 articles). Co-citation analysis identified Orhan Kaan, Abu Patricia Angela R., and Falk Schwendicke as the most cited authors. Keyword analysis revealed "periodontitis," "machine learning," and "artificial intelligence" as core research foci, while burst detection indicated "progression" and "expression" as emerging thematic directions. This study provides a systematic overview of the research landscape, highlighting evolving trends, key contributors, and knowledge structure in AI applications for periodontal disease. The findings offer valuable insights to help dentists and researchers understand current applications, identify frontiers, and potentially guide the future clinical translation of AI technologies in periodontology.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.