Accuracy of Artificial Intelligence-Based Photographic Detection of Gingivitis.

ABSTRACT:

Objectives

Gingivitis is one of the most prevalent plaque-initiated dental diseases globally. It is challenging to maintain satisfactory plaque control without continuous professional advice. Artificial intelligence may be used to provide automated visual plaque control advice based on intraoral photographs.

Methods

Frontal view intraoral photographs fulfilling selection criteria were collected. Along the gingival margin, the gingival conditions of individual sites were labelled as healthy, diseased, or questionable. Photographs were randomly assigned as training or validation datasets. Training datasets were input into a novel artificial intelligence system and its accuracy in detection of gingivitis including sensitivity, specificity, and mean intersection-over-union were

SUBMITTER: Chau RCW 

PROVIDER: S-EPMC10509417 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature