Deep Learning for Detecting Dental Plaque and Gingivitis From Oral Photographs: A Systematic Review.

ABSTRACT:

Objectives

This systematic review aimed to evaluate the performance of deep learning (DL) models in detecting dental plaque and gingivitis from red, green, and blue (RGB) intraoral photographs.

Methods

A comprehensive literature search was conducted across Medline, Scopus, Embase, and Web of Science databases up to January 31, 2025. The methodological characteristics and performance metrics of studies developing and validating DL models for classification, detection, or segmentation tasks were analysed. The risk of bias was assessed using the quality assessment of diagnostic accuracy studies 2 (QUADAS-2) tool, and the certainty of the evidence was evaluated with the grading of recommendations assessment, development, and evaluation (GRADE) framework.

Results

From 3307

SUBMITTER: Moharrami M 

PROVIDER: S-EPMC12627268 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature