ArticleThe Japanese dental science review2026
Mapping the structure of an emerging field: A scientometric decoding of large language model applications in the dental field.
Article in The Japanese dental science review, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
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Who cites it
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Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: To map the knowledge structure of large language model (LLM) applications in the dental field (LADF) through a dual-database scientometric study that highlights trends, collaborations, hotspots, and future directions. Materials and methods: The Web of Science and Scopus were searched on August 1, 2025. LLM-related articles in dentistry were screened. After removing duplicates, 311 English articles and reviews were included in the study. Bibliometrix (v5.0) was used for characteristic and citation analyses. CiteSpace (v6.4.R1) was used for keyword analysis. Results: The number of publications surged from 24 (2023) to 182 (Jan-Aug 2025). Among all publications, 90% were original research articles. Two-thirds were open-access, funded mainly by governments. As for the collaboration network, author and institutional networks were fragmented. National-level collaboration was stronger. High-income countries dominated the LADF output. Keyword clustering revealed a hub-and-spoke structure that included three research frontiers: 1. broadening applications, 2. deepening clinical use, and 3. comparative evaluation, with accuracy and quality as central themes. Conclusions: LADF has expanded rapidly, but research remains fragmented. Shared datasets, stronger global collaboration, and the development of standardized evaluation metrics, particularly for diagnostic and question-answering proficiencies, are necessary to address the central themes of accuracy and quality.
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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 OpenQuestion graph.