Dental Health

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 classifying cervical vertebral maturation (CVM) stages. METHODS: A dataset of 799 cephalometric radiographs, originally obtained for orthodontic diagnosis, was analyzed. For each image, a rectangular section including the second to fourth cervical vertebrae...

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 interpretation of clinical images. Moreover, the use of deep learning has become imbedded within orthodontics with attempts to utilise this approach in informing treatment planning. The aim of this study was to develop and test an AI-based tool capa...

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 ...

Development of a deep learning classification model using a codeless platform for orthodontic extraction decision-making: Impact of image type on model performance.

OBJECTIVES: To evaluate the effect of image type on the performance of a deep learning classification model for decision-making in orthodontic treatme...

Multi-view deep learning for mandibular landmark localization.

OBJECTIVES: Accurate localization of anatomical landmarks on the mandible is crucial for maxillofacial surgery and orthodontic treatment planning. Thi...

Chatbot content analysis of patient information on orthodontic tooth extractions.

INTRODUCTION: This study aims to evaluate the quality, accuracy, readability, and understandability of patient information provided by various Artific...

A semi-automated assessment tool for craniofacial landmarks in CBCT: InVivo7 software.

OBJECTIVES: This study describes and evaluates the functionality of the InVivo7 3D imaging software as a semi-automated tool for identifying craniofac...

Self-reported periodontitis: A multiethnic community-based validation study.

OBJECTIVE: Self-reported periodontal measures offer a practical alternative to clinical examinations in large-scale studies, but few validation effort...

Deep learning-based tooth segmentation for enhanced visualization of dental anomalies and pathologies.

BACKGROUND: This study aimed to developed and validated a deep-learning method for instance-level tooth segmentation in CBCT to enhance visualization ...

Accuracy of Cephalometric Analysis in Cleft Lip and Palate: Comparison of Manual, Artificial Intelligence-Based, and Examiner-Corrected Artificial Intelligence Approaches.

ObjectiveTo evaluate the accuracy of the artificial intelligence (AI)-powered orthodontic imaging system OrthoDx™ for cephalometric analysis in patien...

Prediction of unerupted canine and premolars width using artificial intelligence compared with Tanaka-Johnston and Moyers methods: A retrospective observational analytical study on Iranian population.

INTRODUCTION: Accurate prediction of unerupted teeth widths significantly contributes to formulating optimal treatment plan during mixed dentition pha...

Machine Learning-Based Transcriptomic Diagnosis of Periodontitis.

BACKGROUND: Periodontitis, a prevalent chronic inflammatory disease, remains a global health challenge with conventional diagnostic methods hindered b...

Corrigendum to 'Decoding Epigenetic Enhancer-Promoter Interactions in Periodontitis via Transformer-GAN: A Deep Learning Framework for Inflammatory Gene Regulation and Biomarker Discovery' [International Dental Journal Volume 75, Issue 6, December 2025, 103879].

Graph-Contrastive Convolutional Neural Network for Extracting and Classifying Peptide-Based Periodontal Immunomodulatory and Anti-Inflammatory Signatures.

INTRODUCTION: Periodontitis is a chronic inflammatory disease that occurs when the body's immune system fails to respond properly to microbial biofilm...

Transcription Accuracy of Automatic Speech Recognition for Orthodontic Clinical Records.

Accurate clinical records are fundamental to dental practice. Automatic speech recognition (ASR) has the capacity to convert spoken clinical language ...

Single-Cell and Machine Learning Analysis Reveal Novel Inflammatory Macrophage Subtypes and Biomarkers in Periodontitis.

BACKGROUND: Periodontitis (PD) is a chronic inflammatory disease marked by immune dysregulation and progressive tissue destruction. Macrophages play a...

Dental Crowding Categorization Network (DCC-Net): Explainable deep learning system for automatic categorization of dental crowding on intraoral photographs.

OBJECTIVE: Since categorization of dental crowding is a crucial parameter in orthodontic diagnosis and tooth-extraction decisions, we aimed to develop...