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Diagnostic Accuracy of Oral Images, OPGs, Biomarkers and Questionnaires vs. Clinical Assessment for Periodontal Disease (PostNCT07164573)

Shanghai Ninth People's Hospital Affiliated to Shanghai Jiao Tong University · 2026
ClinicalTrials.gov · Datasets · License: Public Domain · 2026
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diagnosismachine-learningperiodontal-diseaseperiodontitisphotographyradiography
This multi-center, cross-sectional diagnostic trial evaluates the accuracy of multiple non-invasive screening tools-including self-reported questionnaires, intra-oral photographs, orthopantomographs (OPGs), intraoral scans (IOS), and salivary/microbial biomarkers-for detecting periodontal health and diseases (gingivitis and periodontitis Stages I-IV), using full-mouth clinical periodontal examination as the reference standard. A total of 2,000 participants will be recruited across five international centers. Diagnostic performance (sensitivity, specificity, AUROC) of individual and combined methods will be assessed using logistic regression and machine learning algorithms to establish an optimized multi-modal screening algorithm.
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