Dental Health

Suitability of machine learning models for prediction of clinically defined Stage III/IV periodontitis from questionnaires and demographic data in Danish cohorts.

AIM: To evaluate if, and to what extent, machine learning models can capture clinically defined Stage III/IV periodontitis from self-report questionnaires and demographic data.

Orthodontic craniofacial pattern diagnosis: cephalometric geometry and machine learning.

Efficient and reliable diagnosis of craniofacial patterns is critical to orthodontic treatment. Although machine learning (ML) is time-saving and high-precision, prior knowledge should validate its reliability. This study proposed a craniofacial ML diagnostic workflow base on a cephalometric geometric model through clinical verification. A cephalometric geometric model was established to determine...

Deep learning for the early identification of periodontitis: a retrospective, multicentre study.

AIM: To develop a deep-learning model to help general dental practitioners diagnose periodontitis accurately and at an early stage.

Evaluation of AI Model for Cephalometric Landmark Classification (TG Dental).

The accuracy of cephalometric landmark identification for malocclusion classification is essential for diagnosis and treatment planning. Identifying t...

The knowledge, experience, and attitude on artificial intelligence-assisted cephalometric analysis: Survey of orthodontists and orthodontic students.

INTRODUCTION: Artificial intelligence (AI) developed rapidly in orthodontics, and AI-based cephalometric applications have been adopted. This study ai...

Development and accuracy of artificial intelligence-generated prediction of facial changes in orthodontic treatment: a scoping review.

Artificial intelligence (AI) has been utilized in soft-tissue analysis and prediction in orthodontic treatment planning, although its reliability has ...

Clinical and oral microbiome pattern of halitosis patients with periodontitis and gingivitis.

Halitosis is caused by a bacterial proteolytic process that induces the production of volatile sulfur compounds, odor-causing gases. The aim of this s...

In-vivo evaluation of Artificial Intelligence Driven Remote Monitoring technology for tracking tooth movement and reconstruction of 3-dimensional digital models during orthodontic treatment.

INTRODUCTION: An in-vivo evaluation of the Dental Monitoring (DM; Paris, France) Artificial Intelligence Driven Remote Monitoring technology was condu...

Biomechanical simulation of forces and moments of initial orthodontic tooth movement in dependence on the used archwire system by ROSS (Robot Orthodontic Measurement & Simulation System).

OBJECTIVES: Aim of this study was to determine the forces and moments during simulated initial orthodontic tooth movements using a novel biomechanical...

Modeling contact forces during human-robot interactions for performing activities of daily living.

This study aims to characterize contact forces between humans and tools during activities of daily living (ADL) to provide information to a personal c...

A family-centered orthodontic screening approach using a machine learning-based mobile application.

BACKGROUND/PURPOSE: Skeletal orthodontic deformities can have functional and aesthetic consequences, making early detection critical. This study aimed...

A machine learning model for orthodontic extraction/non-extraction decision in a racially and ethnically diverse patient population.

INTRODUCTION: The purpose of the present study was to create a machine learning (ML) algorithm with the ability to predict the extraction/non-extracti...

An artificial neural network approach for rational decision-making in borderline orthodontic cases: A preliminary analytical observational in silico study.

INTRODUCTION: Artificial intelligence (AI) technology has transformed the way healthcare functions in the present scenario. In orthodontics, expert sy...

Effectiveness of AI-driven remote monitoring technology in improving oral hygiene during orthodontic treatment.

OBJECTIVE: This study aimed to evaluate the effectiveness of Dental Monitoring™ (DM™) Artificial Intelligence Driven Remote Monitoring Technology (AID...

Diagnostic Test Accuracy of Artificial Intelligence in Detecting Periapical Periodontitis on Two-Dimensional Radiographs: A Retrospective Study and Literature Review.

This study aims to evaluate the diagnostic accuracy of artificial intelligence in detecting apical pathosis on periapical radiographs. A total of twen...

XGBoost-aided prediction of lip prominence based on hard-tissue measurements and demographic characteristics in an Asian population.

INTRODUCTION: Prediction of lip prominence based on hard-tissue measurements could be helpful in orthodontic treatment planning and has been challengi...

Diagnostic accuracy of AI in orthodontic extraction decisions: "Are we ready to let Mr. Data run our Enterprise?" A commentary on a systematic review.

OBJECTIVE: To collect evidence on the ability of artificial intelligence programs to accurately make extraction decisions in orthodontic treatment pla...

Prospective cohort study on mesh shrinkage measured with MRI after robot-assisted minimal invasive retrorectus ventral hernia repair using an iron-oxide-loaded polyvinylidene fluoride mesh.

BACKGROUND: Mesh-reinforced ventral hernia repair is considered the gold standard treatment for all but the smallest of hernias. Human data on mesh sh...

High-performance and low-power source-gated transistors enabled by a solution-processed metal oxide homojunction.

Cost-effective fabrication of mechanically flexible low-power electronics is important for emerging applications including wearable electronics, artif...

Artificial Intelligence for Detecting Cephalometric Landmarks: A Systematic Review and Meta-analysis.

Using computer vision through artificial intelligence (AI) is one of the main technological advances in dentistry. However, the existing literature on...