BACKGROUND: Oral microbiota is a major etiological factor in the development of dental caries. Next-generation sequencing techniques have been widely used, generating vast amounts of data which is underexplored. The advancement of artificial intellig...
OBJECTIVE: Dental electronic health records (EHRs) often lack comprehensive data for evaluating procedure outcomes. Machine learning (ML) enables predictive modeling but its applicability to dental EHR data remains unclear. This study assessed the re...
OBJECTIVES: Deep convolutional neural networks (CNNs) are advancing rapidly in medical research, demonstrating promising results in diagnosis and prediction within radiology and pathology. This study evaluates the efficacy of deep learning algorithms...
BACKGROUND: Early childhood caries (ECC) is a widespread pediatric dental condition that is influenced by a combination of biological, behavioral, and demographic factors. Salivary biomarkers, including beta-defensin-2 (BD-2) and statherin (STATH), o...
Early childhood caries (ECC) exhibits tooth specificity, highlighting the need for single-tooth-level prevention. We profiled 2,504 dental plaque microbiota samples from 89 preschoolers across two cohorts, tracking compositional changes with imputed ...
OBJECTIVES: Dental caries remains a significant global health concern. Recognising the diagnostic potential of cone-beam computed tomography (CBCT) in caries assessment, this study aimed to develop an artificial intelligence (AI)-driven tool for accu...
Journal of esthetic and restorative dentistry : official publication of the American Academy of Esthetic Dentistry ... [et al.]
Apr 7, 2025
OBJECTIVES: The application of deep learning techniques for detecting caries in bitewing radiographs has gained significant attention in recent years. However, the comparative performance of various modern deep learning models and strategies to enhan...
INTRODUCTION: Artificial intelligence (AI) has significantly transformed the diagnosis and treatment of dental caries, a prevalent issue in oral health care. Traditional diagnostic procedures such as eye inspection and radiography have limitations in...
OBJECTIVES: Annotating carious lesions on images is challenging. For artificial intelligence (AI) applications, the aggregation of heterogeneous multi-examiner annotations into one single annotation (e.g. via majority voting, MV) is usually needed. W...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.