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Recruiting NCT06306677

Accuracy of an AI-clinical Knowledge-based Hybrid System for Detecting Periodontitis in OPG Images

Trial Parameters

Condition Periodontitis
Sponsor Shanghai Ninth People's Hospital Affiliated to Shanghai Jiao Tong University
Study Type OBSERVATIONAL
Phase N/A
Enrollment 1,200
Sex ALL
Min Age 18 Years
Max Age N/A
Start Date 2024-03-12
Completion 2024-08-01
Interventions
AI-clincial-based hybrid system for radiographic image analysis

Brief Summary

Periodontitis is highly prevalent and rarely detected and treated in the earlier stages of the disease. Orthopantomography (OPG) is the most frequently taken dental radiograph around the world, and its systematic screening may contribute to early detection of periodontitis and access to the needed level of care. The investigators' recent study initially developed an AI-clinical knowledge-based system for automatic periodontitis diagnosis and indicated good performance for differentiating stage II-IV periodontitis. This cross-sectional diagnostic study aims to compare the diagnostic accuracy of this AI-clinical knowledge-based hybrid system (Index test) with human experts (reference test) for differentiating stage II-IV periodontitis using the OPG images obtained from different 4 centers around the world.

Eligibility Criteria

Inclusion Criteria: 1. Aged 18 and above 2. Having taken the OPG image Exclusion Criteria: 1. Edentulous mouth

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