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ABSTRACT: Background
Periodontitis (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.Methods
Microbial 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 algori
SUBMITTER: Zhao Z
PROVIDER: S-EPMC11976633 | biostudies-literature | 2025 Apr
REPOSITORIES: biostudies-literature