AIMC Topic: Dental Plaque

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Deep learning for automated dental plaque index assessment: validation against expert evaluations.

BMC oral health
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...

Single-tooth resolved, whole-mouth prediction of early childhood caries via spatiotemporal variations of plaque microbiota.

Cell host & microbe
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
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
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
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
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
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
AIM: To determine the efficacy of tricalcium phosphate (TCP) and calcium sucrose phosphate (CSP) on the inhibition of .

Deep learning-based dental plaque detection on primary teeth: a comparison with clinical assessments.

BMC oral health
BACKGROUND: Dental plaque causes many common oral diseases (e.g., caries, gingivitis, and periodontitis). Therefore, plaque detection and control are extremely important for children's oral health. The objectives of this study were to design a deep l...

Comparison of Boiling and Robotics Automation Method in DNA Extraction for Metagenomic Sequencing of Human Oral Microbes.

PloS one
The rapid improvement of next-generation sequencing performance now enables us to analyze huge sample sets with more than ten thousand specimens. However, DNA extraction can still be a limiting step in such metagenomic approaches. In this study, we a...