Development and validation of artificial intelligence models for automated periodontitis staging and grading using panoramic radiographs.

ABSTRACT:

Background

Periodontal diseases are common chronic conditions that can lead to tooth loss and systemic complications if not diagnosed and treated promptly. The 2017 classification by the American Academy of Periodontology highlights the need for effective, accurate diagnostic tools. This study aimed to develop and validate an AI-driven system for automated staging and grading periodontitis from panoramic radiographs using the YOLOv8 architecture.

Methods

A total of five hundred panoramic radiographs from patients diagnosed with periodontitis were included. Radiographs were labeled and split into training (75%), validation (15%), and testing (10%) sets. Three specialized YOLOv8-based models were trained to segment the alveolar bone level, the cemento-enamel junction (CEJ), an

SUBMITTER: Do KQ 

PROVIDER: S-EPMC12522615 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature