AIMC Topic: Dental Caries

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Caries lesions diagnosis with deep convolutional neural network in intraoral QLF images by handheld device.

BMC oral health
OBJECTIVES: This study investigated the effectiveness of a deep convolutional neural network (CNN) in diagnosing and staging caries lesions in quantitative light-induced fluorescence (QLF) images taken by a self-manufactured handheld device.

Classification of Caries Based on CBCT: A Deep Learning Network Interpretability Study.

Journal of imaging informatics in medicine
This study aimed to create a caries classification scheme based on cone-beam computed tomography (CBCT) and develop two deep learning models to improve caries classification accuracy. A total of 2713 axial slices were obtained from CBCT images of 204...

AI-Assisted Detection of Interproximal, Occlusal, and Secondary Caries on Bite-Wing Radiographs: A Single-Shot Deep Learning Approach.

Journal of imaging informatics in medicine
Tooth decay is a common oral disease worldwide, but errors in diagnosis can often be made in dental clinics, which can lead to a delay in treatment. This study aims to use artificial intelligence (AI) for the automated detection and localization of s...

Simultaneous detection of dental caries and fissure sealant in intraoral photos by deep learning: a pilot study.

BMC oral health
BACKGROUND: Deep learning, as an artificial intelligence method has been proved to be powerful in analyzing images. The purpose of this study is to construct a deep learning-based model (ToothNet) for the simultaneous detection of dental caries and f...

Predicting dental caries outcomes in young adults using machine learning approach.

BMC oral health
OBJECTIVES: To predict the dental caries outcomes in young adults from a set of longitudinally-obtained predictor variables and identify the most important predictors using machine learning techniques.

Performance comparison of multifarious deep networks on caries detection with tooth X-ray images.

Journal of dentistry
OBJECTIVES: Deep networks have been preliminarily studied in caries diagnosis based on clinical X-ray images. However, the performance of different deep networks on caries detection is still unclear. This study aims to comprehensively compare the car...

Artificial intelligence for caries detection: a novel diagnostic tool using deep learning algorithms.

Oral radiology
OBJECTIVES: The aim of this study was to develop an assessment tool for automatic detection of dental caries in periapical radiographs using convolutional neural network (CNN) architecture.

AI-Dentify: deep learning for proximal caries detection on bitewing x-ray - HUNT4 Oral Health Study.

BMC oral health
BACKGROUND: Dental caries diagnosis requires the manual inspection of diagnostic bitewing images of the patient, followed by a visual inspection and probing of the identified dental pieces with potential lesions. Yet the use of artificial intelligenc...

Early childhood caries detection using smartphone artificial intelligence.

European archives of paediatric dentistry : official journal of the European Academy of Paediatric Dentistry