AIMC Topic: Dental Caries

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Accuracy of deep learning-based AI models for early caries lesion detection: the influence of annotation quality and reference choice.

Clinical oral investigations
OBJECTIVES: The objective of this study is to assess how different annotation methods used during AI model training affect the accuracy of early caries lesion detection, and how the choice of the evaluation reference standard leads to significant dif...

Diagnostic competence of senior dental students in detecting caries on panoramic radiographs with and without artificial intelligence assistance: a cross-sectional studycaries detection on panoramic radiographs.

BMC medical education
PURPOSE: Accurate detection of proximal dental caries on panoramic radiographs is essential for effective treatment planning and preventive care. While senior dental students gradually develop interpretative competence during their training, artifici...

Bio-inspired neutrosophic-enzyme intelligence framework for pediatric dental disease detection using multi-modal clinical data.

Scientific reports
Pediatric oral diseases affect over 60% of children globally, yet current diagnostic approaches lack precision and speed necessary for early intervention. This study developed a novel bio-inspired neutrosophic-enzyme intelligence framework integratin...

Tooth-to-white spot lesion YOLO: a novel model for white spot lesion detection.

BMC oral health
BACKGROUND: To develop a new deep learning model for detecting white spot lesions (WSLs), which are commonly observed in patients undergoing orthodontic treatment, and assess its accuracy.

Development and validation of diagnostic and prognostic prediction tools for dental caries in young children through prospective and cross-sectional observational studies: a protocol.

BMJ open
INTRODUCTION: Dental caries is the most common oral disease worldwide, affecting up to 90% of children globally. It can lead to pain, infection and impaired quality of life. Early prevention is a key strategy for reducing the prevalence of dental car...

Clinical application of deep learning for enhanced multistage caries detection in panoramic radiographs.

Scientific reports
The detection of dental caries is typically overlooked on panoramic radiographs. This study aims to leverage deep learning to identify multistage caries on panoramic radiographs. The panoramic radiographs were confirmed with the gold standard bitewin...

Metagenomic research on the structural difference of plaque microbiome from different caries stages and the construction of a caries diagnostic model.

mSystems
Development of dental caries is a dynamic process; yet, there is limited knowledge on microbial differences at various stages of caries at higher resolution. To investigate the shifting microbiome profiles across different caries stages, 30 children ...

A Machine Learning Algorithm With an Oversampling Technique in Limited Data Scenarios for the Prediction of Present and Future Restorative Treatment Need: Development and Validation Study.

JMIR medical informatics
BACKGROUND: Untreated dental caries is the most common health condition worldwide. Therefore, new strategies need to be developed to reduce the manifestations of dental caries.

Development and validation of a novel public prediction platform for deciduous caries in preschool children: an observational study from Northwest China.

BMC pediatrics
BACKGROUND: Early childhood caries (ECC) is a major global public health concern, necessitating its early screening. This study aimed to establish a caries risk assessment (CRA) platform for managing caries in community preschool children in underdev...

Identification of cariogenic bacteria by click chemistry mediated polyethylene glycolized graphyne nanozymes.

Mikrochimica acta
Dental caries, one of the most common oral diseases, is mainly induced by multiple cariogenic bacteria in the oral microenvironment, so it is important to construct a method that can identify oral multiply cariogenic bacteria. Herein, a machine learn...