Dental Health

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 test setup.

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 care robot. The study was conducted on non-impaired subjects to capture various static and dynamic force levels when making contact with three different robotic tools, each designed to perform an ADL task: hair brushing, face wiping, and face shaving....

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...

Effectiveness of cone-beam computed tomography-generated cephalograms using artificial intelligence cephalometric analysis.

Lateral cephalograms and related analysis constitute representative methods for orthodontic treatment. However, since conventional cephalometric radio...

Neural network ensemble model for prediction of erythrocyte sedimentation rate (ESR) using partial least squares regression.

The erythrocyte sedimentation rate (ESR) is a non-specific blood test for determining inflammatory conditions. However, the long measurement time (60 ...

Quantification and comparison of the regional acceleratory phenomenon in bone following piezosurgery or bur osteotomy: A pilot study in rats.

BACKGROUND/OBJECTIVE: The Regional Acceleratory Phenomenon (RAP) can be induced surgically via decortication (selective cortical penetrations) of bone...

Electrostatic Adhesion Clutch with Superhigh Force Density Achieved by MXene-Poly(Vinylidene Fluoride-Trifluoroethylene-Chlorotrifluoroethylene) Composites.

Electrostatic adhesion (EA) clutches are widely applied in robots, wearable devices, and virtual reality, due to their compliance, lightweight, ultrat...

Two-Stage Mesh Deep Learning for Automated Tooth Segmentation and Landmark Localization on 3D Intraoral Scans.

Accurately segmenting teeth and identifying the corresponding anatomical landmarks on dental mesh models are essential in computer-aided orthodontic t...

Application of deep learning artificial intelligence technique to the classification of clinical orthodontic photos.

BACKGROUND: Taking facial and intraoral clinical photos is one of the essential parts of orthodontic diagnosis and treatment planning. Among the diagn...

Accuracy of artificial intelligence for tooth extraction decision-making in orthodontics: a systematic review and meta-analysis.

OBJECTIVE: This study aimed to analyze the accuracy of artificial intelligence (AI) for orthodontic tooth extraction decision-making.

Automated detection of smiles as discrete episodes.

BACKGROUND: Patients seeking restorative and orthodontic treatment expect an improvement in their smiles and oral health-related quality of life. None...