Dental Health

Deep learning cone-beam computed tomography image segmentation for the 3D visualization of mandibular infraosseous periodontal defects.

BACKGROUND: The accurate assessment of infraosseous periodontal defects is crucial for effective diagnosis and treatment planning. Cone-beam computed tomography (CBCT) enables detailed imaging of these defects; however, to leverage their full potential, CBCT images must be reconstructed in 3 dimensions (3D). Manual and semi-automatic (SA) segmentation methods are time-consuming and prone to human ...

Nanointerface-Engineered Triboelectric Nanocomposite for Self-Powered Intelligent Motion Decoding.

Real-time motion intelligence from wearable systems requires efficient conversion of biomechanical energy into stable and information-rich electrical signals. However, conventional triboelectric sensors often suffer from limited interfacial polarization efficiency and unstable output under complex mechanical deformation. Here, we present a self-powered triboelectric wristband enabled by nanointerf...

YOLOv10-based deep learning model for dental plaque object detection in intraoral photographs of orthodontic patients.

Development of Leading Enhancement Assistive Planning: A three-dimensional tooth classification system for orthodontic treatment with clear aligners.

OBJECTIVE: To develop and validate the Leading Enhancement Assistive Planning (LEAP) system, a deep learning-based tool for automated malocclusion cla...

Deep learning-based segmentation of enamel, cementum, alveolar bone, and gingiva in periodontal ultrasound images.

OBJECTIVES: To develop a deep learning-based multi-class segmentation model for the simultaneous segmentation of key periodontal structures, including...

Automated periodontitis diagnosis and staging using an end-to-end deep learning model on panoramic dental radiographs.

Comparative evaluation of ChatGPT and Gemini artificial intelligence in patient education on clear aligner therapy.

OBJECTIVES: To compare the performance of ChatGPT-4 Turbo and Gemini 1.5 Pro in the domain of Clear Aligner Therapy (CAT). MATERIALS AND METHODS: A to...

Artificial intelligence in healthcare, dentistry, and orthodontics; is it an opportunity or a threat? An epistemological review.

Helpless, the human race stands in front of Artificial Intelligence (AI) that has invaded us and evaded our defences, leaving the world stranded and s...

Unsupervised phenotyping of the periodontal architecture through high-dimensional clustering of electronic health records: A multicenter study.

BACKGROUND: To identify novel periodontal phenotypes using unsupervised machine learning on a large-scale, multicenter cohort, specifically characteri...

Artificial Intelligence Enabled Precise 3D Printing of Polyvinylidene Fluoride (PVDF) Microfibers for Ultrasensitive Sensors.

The pursuit of sustainable green energy has intensified the demand for self-powered materials, which are capable of efficiently converting ambient mec...

Relationships between periodontitis and inflammatory bowel disease: Screening and functional analysis of endoplasmic reticulum stress-related biomarkers.

This study aimed to explore the relationship between periodontitis (PD) and inflammatory bowel disease (IBD), focusing on changes in the expression of...

Proteomic Characterization of Grade II Furcation Defects: A Discovery-Phase Study.

This study analyzed the gingival crevicular fluid (GCF) proteome of 35 patients with Grade II furcation defects using the Olink Reveal platform. Compa...

Integrated machine learning and geochemical modeling reveal hydrogeochemical controls on fluoride and arsenic co-contamination in groundwater.

Groundwater contamination by fluoride (F⁻) and arsenic (As) is a serious environmental issue and poses significant human health risks in many developi...

Predicting Longitudinal Caries Trajectories from Childhood to Early Adulthood.

Prior studies have used traditional trajectory analyses to classify caries progression; however, none have applied machine learning (ML) to predict ca...

Data-Driven Tooth Selection Enhances Partial-Mouth Periodontal Screening.

The high prevalence of periodontitis has imposed a significant global disease burden. Epidemiologic surveys rely on full-mouth periodontal examination...

Lightweight liquid neural networks decipher salivary metabolic fingerprinting for high-risk periodontitis screening in diabetes.

Type 2 diabetes (T2DM) and periodontitis are bidirectionally linked diseases that both involve chronic inflammation; their co‑occurrence represents a ...

Dual biomarkers ALOX5AP and INPP4A are associated with lipid metabolism and neutrophil extracellular traps in periodontitis: A bioinformatics and clinical validation study.

OBJECTIVE(S): Periodontitis is a chronic inflammatory disease characterized by progressive alveolar bone destruction. While lipid metabolism and neutr...

Development and Validation of a Machine Learning-Based Model to Predict Peri-Implant Mucositis in Patients With Dental Implant Placement After 1-Year.

OBJECTIVES: To develop and validate an interpretable machine learning (ML) model for early prediction of peri-implant mucositis (PIM). MATERIAL AND ME...

Evaluating the Artificial Intelligence Driven Monitoring System Notifications: Clear Aligner and Oral Hygiene Perspectives.

INTRODUCTION: The widespread use of smartphones presents a remarkable opportunity for real-time management of orthodontic treatment. The development o...

An Interpretable Fuzzy-AI Clinical Decision Support System for Selecting Orthognathic Surgery in Skeletal Class III Malocclusion.

This study aimed to develop an interpretable fuzzy-artificial intelligence (AI) framework to support treatment decision-making between orthognathic su...