Dental Health

Automated landmark detection on lateral photographs using artificial intelligence: diagnostic accuracy compared to expert annotations.

PURPOSE: Lateral photographs are routinely evaluated as part of orthodontic diagnostics and treatment planning. Anthropometric measurements based on soft tissue landmarks are taken to evaluate facial features and attractiveness. The detection of these landmarks is a process performed by specialists and prone to intra- and inter-annotator variability. The aims of this investigation were (1) to trai...

Exploration Novel Therapeutic Targets for Periodontitis via Stress Granules Biomarkers.

BACKGROUND: Periodontitis (PD) is associated with stress granules (SGs), which are involved in cellular stress responses. Identifying biomarkers related to SGs in PD is key to grasping its pathogenesis and devising novel therapeutic approaches. METHODS: Microarray datasets GSE10334 and GSE106090 were downloaded from public databases, and experimental verification was conducted. Differentially expr...

Fully automatic AI diagnosis of alveolar bone defect in anterior teeth on CBCT images.

OBJECTIVE: To develop a fully automatic artificial intelligence (AI) system for diagnosing alveolar bone defects (ABDs) in anterior teeth on cone-beam...

Bi-level alignment with super-resolution head for unsupervised cephalometric landmark localization.

Objective. Cephalometric alandmark localization is of great clinical significance in diagnosing and treating patients with dental-maxillofacial deform...

SERPINA1 as a Shared Biomarker in Periodontitis and Oral Squamous Cell Carcinoma.

OBJECTIVE: Periodontitis (PD) and oral squamous cell carcinoma (OSCC) frequently co‑occur in clinical populations. However, shared molecular determina...

Deep learning-based automatic adenoid segmentation and a novel volume-based index for adenoid hypertrophy assessment.

BACKGROUND: Adenoid hypertrophy is a common cause of pediatric obstructive sleep apnea (OSA), which can impair cognitive development and affect cranio...

Multi-task non-contact ballistocardiogram-based vital signs monitoring in acupuncture.

The study introduces an innovative approach for efficient vital signs monitoring in acupuncture by combining multi-channel ballistocardiogram (BCG) si...

Towards automated model analysis: A multiview AI segmentation of 3D dental scans.

OBJECTIVE: Precise identification of tooth and gingival boundaries in digital models is essential for effective orthodontic diagnosis, treatment plann...

Oral-Rinse-Sourced Microbiota in Oral Health and Diseases in a Representative US Adult Population: Implications for Diagnostics.

AIMS: To investigate the associations between oral-rinse microbiota and distinct oral conditions, and further evaluate its potential ability to distin...

A hybrid MMBERT framework for classifying periodontal bone loss: Integrating visual and textual information.

INTRODUCTION: Periodontitis, a chronic inflammatory disease, causes bone loss and tooth instability. Early diagnosis, aided by clinical and radiograph...

An artificial intelligence-assisted automated quantitative evaluation system for condylar morphological changes of temporomandibular joint.

OBJECTIVES: To develop an artificial intelligence (AI)-assisted system for the automated quantitative evaluation of temporomandibular joint (TMJ) cond...

Multi-Architecture deep learning for CBCT segmentation of dental hard tissues and pulp in mixed dentition.

OBJECTIVE: To develop and evaluate deep learning-based 3D models (CNN, Transformer, and Mamba architectures) for automated segmentation of pulp, prima...

Investigating the mechanism of berberine in inhibiting periodontitis progression using machine learning, molecular docking, and experimental validation.

BACKGROUND: Periodontitis is a chronic inflammatory disease characterized by the destruction of periodontal tissues. Berberine (BBR), a natural alkalo...

AI-driven gingival segmentation on CBCT: Validation using delineation by intraoral scanning and CBCT-based cotton roll separation.

OBJECTIVES: To validate a novel AI approach for automated gingival segmentation directly from cone beam computed tomography (CBCT) scans acquired with...

Impact of image processing techniques on deep learning-based classification accuracy of cervical vertebral maturation.

OBJECTIVES: This research aimed to investigate how different image processing techniques influence the performance of a deep learning model in classif...

The development of an image processing model to estimate tooth width and space requirements.

OBJECTIVES: The advent of machine and deep learning has raised the possibility of increased efficiency and indeed improved accuracy in relation to the...

Exosome-related lactylation gene signature defines diagnostic biomarkers of periodontitis through integrative bulk and single-cell transcriptomics.

BACKGROUND: Exosomes and lactylation modification have been increasingly recognized as key regulators of diseases, yet their integrative role in perio...

Delayed Dental Development in Children With Non-Syndromic Hypodontia: A Cross-Sectional Study Using a Machine Learning Approach to Dental Age Estimation.

OBJECTIVES: To investigate the influence of non-syndromic hypodontia on radiographic dental development and to estimate dental age in children with bi...

Machine Learning-Based Prediction Model for Alveolar Bone Defect Risk Following Orthodontic Treatment.

OBJECTIVES: Alveolar bone defects, such as fenestration and dehiscence, induced by orthodontic treatment represent significant complications that can ...

Sociodemographic Predictors of Child-Parent Agreement on Oral Health.

BACKGROUND: Oral health is vital for children's overall well-being. Parents play a critical role in shaping children's oral health through preventive ...