ArticleInternational dental journal2025
Oral Microbe Community and Pyramid Scene Parsing Network-based Periodontitis Risk Prediction.
Article in International dental journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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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
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial Intelligence in Periodontology: A Systematic Review.Journal of periodontal research · 2026Pooled it
- FAM30A Induces Inflammation and Oxidative Damage in PDLSCs by Targeting miR-424-5p.International dental journal · 2026Article
- Association of Gingival Crevicular Fluid Leptin Levels With Stages of Periodontitis: A Cross-Sectional Study.International dental journal · 2026Article
- Interrogation of imaging-based interspecies dynamics in the oral microbiome.Journal of oral microbiology · 2026Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPeriodontitis (PD) is a common chronic inflammatory disease affecting the gums and supporting tooth structures. It is often diagnosed only after significant irreversible tissue damage - such as gum recession and bone loss - has occurred, leading to tooth loss and systemic complications. Early detection of PD risk is therefore critical. This study integrates the Pyramid Scene Parsing Network (PSPNet), a deep learning model, with dental plaque microbial profiling data to generate a Periodontitis Risk Score (PRS) for identifying individuals at high risk of developing PD.
methodsMicrobial profiling data from dental plaque samples of 90 healthy controls (CON) and 514 PD patients were obtained from the Gene Expression Omnibus database (GSE32159). A preprocessing algorithm identified predictive indicators for PD and calculated actual PRS values (PRS
resultsAfter preprocessing, 27 indicators were identified for PD risk prediction. The PRS
conclusionBy combining microbial profiling with PSPNet, this study offers a reliable, efficient, and noninvasive method for early screening of individuals at high risk of PD. This approach can help prevent irreversible periodontal damage, improve oral health, and reduce the associated health and economic burdens.
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Registered trials
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