Evidence map›Paper›PMID 41236841›Full record

ArticleJournal of dental education2026

Integrating Clinical and Systemic Knowledge in Periodontal and Peri-Implant Disease Education Through a Knowledge Graph.

Yi-Jia Sun, Yi-Feng Zhao, Lei Zhang, Li-Jun Luo, Yue Zhou, Yan Zhang, Xue Han, Min Zhou

Abstract read
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In one paragraph

Article in Journal of dental education, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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.

2 · The registry

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3 · Its place in the literature

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Yi-Jia SunShanghai Engineering Research Center of Tooth Restoration and Regeneration & Tongji Research Institute of Stomatology & Department of Periodontology, Shanghai Tongji Stomatological Hospital and Dental School, Tongji University, Shanghai, China.
Yi-Feng ZhaoUniversity of Amsterdam, Amsterdam, the Netherlands.
Lei ZhangShanghai Engineering Research Center of Tooth Restoration and Regeneration & Tongji Research Institute of Stomatology & Department of Periodontology, Shanghai Tongji Stomatological Hospital and Dental School, Tongji University, Shanghai, China.
Li-Jun LuoShanghai Engineering Research Center of Tooth Restoration and Regeneration & Tongji Research Institute of Stomatology & Department of Periodontology, Shanghai Tongji Stomatological Hospital and Dental School, Tongji University, Shanghai, China.
Yue ZhouShanghai Engineering Research Center of Tooth Restoration and Regeneration & Tongji Research Institute of Stomatology & Department of Periodontology, Shanghai Tongji Stomatological Hospital and Dental School, Tongji University, Shanghai, China.
Yan ZhangShanghai Engineering Research Center of Tooth Restoration and Regeneration & Tongji Research Institute of Stomatology & Department of Periodontology, Shanghai Tongji Stomatological Hospital and Dental School, Tongji University, Shanghai, China.
Xue HanShanghai Engineering Research Center of Tooth Restoration and Regeneration & Tongji Research Institute of Stomatology & Department of Periodontology, Shanghai Tongji Stomatological Hospital and Dental School, Tongji University, Shanghai, China.
Min ZhouShanghai Engineering Research Center of Tooth Restoration and Regeneration & Tongji Research Institute of Stomatology & Department of Periodontology, Shanghai Tongji Stomatological Hospital and Dental School, Tongji University, Shanghai, China.

Funding

Tongji University
6 · The paper itself

Abstract

aimThis study aims to construct a knowledge graph in the field of periodontology and develop a knowledge-graph-based intelligent question-answering (QA) system, with the goal of enhancing the structured management and intelligent application of periodontal disease knowledge. MATERIALS AND

methodsConsensus documents and evidence-based guidelines from the EFP and AAP served as primary data sources. Entities and relationships related to periodontal diseases were extracted using a large language model-assisted semantic approach to generate structured quintuple data. A knowledge graph was constructed in Neo4j, upon which a graph-enhanced intelligent PerioMind system was developed.

resultsA total of 26 authoritative documents were included, from which 1894 knowledge quintuples were extracted, resulting in a knowledge graph comprising 1872 nodes and 1894 edges. The PerioMind system, developed on top of the graph, demonstrated efficient parsing of natural language queries and the generation of professional responses. The system achieved the following evaluation scores (out of 5): accuracy 4.8, interpretability 4.4, domain relevance 4.8, and completeness 4.5.

conclusionThis study developed a structured knowledge graph and the PerioMind system for periodontology, supporting intelligent diagnosis, education, and research. Future work will expand knowledge coverage and enhance semantic reasoning to advance an intelligent knowledge service platform.

Indexed as

Education, DentalPeriodontal DiseasesPeriodonticsArtificial IntelligenceHumansKnowledge Basesartificial intelligenceknowledge graphperiodontologyquestion‐answering system

Identifiers

PMID41236841
PMCPMC13489181

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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.