We develop a Computer Aided Diagnosis (CAD) system, which enhances the performance
of dentists in detecting wide range of dental caries. The CAD System achieves this by acting …

Objective This study aimed to evaluate a deep learning (DL) system using convolutional
neural networks (CNNs) for automatic detection of caries on bitewing radiographs. Study …

Dental caries is an extremely common problem in dentistry that affects a significant part of
the population. Approximal caries are especially difficult to identify because their position …

The early detection of initial dental caries enables preventive treatment, and bitewing
radiography is a good diagnostic tool for posterior initial caries. In medical imaging, the …

Objective The aim of this work was to assemble a large annotated dataset of bitewing
radiographs and to use convolutional neural networks to automate the detection of dental …

Objectives The aim of this study is to recommend an automatic caries detection and
segmentation model based on the Convolutional Neural Network (CNN) algorithms in dental …

Purpose The aim of this study was to analyse and review deep learning convolutional neural
networks for detecting and diagnosing early-stage dental caries on periapical radiographs …

Objectives: We aimed to assess the impact of an artificial intelligence (AI)-based diagnostic-
support software for proximal caries detection on bitewing radiographs. Methods: A cluster …

Diagnosing dental caries plays a pivotal role in preventing and treating tooth decay.
However, traditional methods of diagnosing caries often fall short in accuracy and efficiency …

This study aimed to evaluate the validity of a deep learning-based convolutional neural
network (CNN) for detecting proximal caries lesions on bitewing radiographs. A total of 978 …