AIMC Topic: Dental Plaque
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Ensemble learning for microbiome-based caries diagnosis: multi-group modeling and biological interpretation from salivary and plaque metagenomic data.
BMC oral health
Jul 17, 2025
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...
Deep learning for automated dental plaque index assessment: validation against expert evaluations.
BMC oral health
Jul 2, 2025
BACKGROUND: The integration of artificial intelligence (AI) into healthcare has led to promising advancements in clinical decision-making and diagnostic accuracy. In dentistry, automated methods to evaluate oral hygiene measures, such as dental plaqu...
Shotgun Metagenomics Identifies in a Cross-Sectional Setting Improved Plaque Microbiome Biomarkers for Peri-Implant Diseases.
Journal of clinical periodontology
Jun 4, 2025
AIM: This observational study aimed to verify and improve the predictive value of plaque microbiome of patients with dental implant for peri-implant diseases.
Single-tooth resolved, whole-mouth prediction of early childhood caries via spatiotemporal variations of plaque microbiota.
Cell host & microbe
May 30, 2025
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 ...
Oral Microbe Community and Pyramid Scene Parsing Network-based Periodontitis Risk Prediction.
International dental journal
Nov 28, 2024
BACKGROUND: Periodontitis (PD) is a common chronic inflammatory disease affecting the gums and supporting tooth structures. It is often diagnosed only after significant irreversible tissue damage - such as gum recession and bone loss - has occurred, ...
DeepPlaq: Dental plaque indexing based on deep neural networks.
Clinical oral investigations
Sep 20, 2024
OBJECTIVES: The selection of treatment for dental plaque is closely related to the condition of the plaque on different teeth. This study validated the ability of CNN models in assessing the dental plaque indices.
Evaluation of Dental Plaque Area with Artificial Intelligence Model.
Nigerian journal of clinical practice
Jun 29, 2024
OBJECTIVES: This study aims to assess the diagnostic accuracy of an artificial intelligence (AI) system employing deep learning for identifying dental plaque, utilizing a dataset comprising photographs of permanent teeth.
Clinical evaluation of Artificial Intelligence Driven Remote Monitoring technology for assessment of patient oral hygiene during orthodontic treatment.
American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics
Feb 15, 2024
INTRODUCTION: This study aimed to clinically evaluate the accuracy of Dental Monitoring's (DM) artificial intelligence (AI) image analysis and oral hygiene notification algorithm in identifying oral hygiene and mucogingival conditions.
Robot and mechanical testing of a specialist manual toothbrush for cleaning efficacy and improved force control.
BMC oral health
Jun 8, 2022
BACKGROUND: Toothbrushes require flexibility to access all dental surfaces and remove plaque effectively, but they should also aim to prevent or limit overbrushing and consequent damage to teeth and gums. In two studies, the physical properties and c...
Effect of Tricalcium Phosphate and Calcium Sucrose Phosphate on the Inhibition of : An Study.
The journal of contemporary dental practice
Dec 1, 2021
AIM: To determine the efficacy of tricalcium phosphate (TCP) and calcium sucrose phosphate (CSP) on the inhibition of .
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