Dental Health

Development of an Artificial Intelligence-Based Algorithm for the Assessment of Skeletal Age and Detection of Cervical Vertebral Anomalies in Patients with Cleft Lip and Palate.

ObjectiveTo develop an artificial intelligence (AI)-based algorithm for the assessment and comparison of skeletal maturation in patients with and without cleft lip and/or palate and to detect the presence of cervical vertebral anomalies (CVAs).DesignRetrospective cohort study.SettingA university orthodontic clinic and comprehensive cleft care centers.Patients/ParticipantsIn total, 1080 cephalogram...

Genetic analysis of potential markers and therapeutic targets for immunity in periodontitis.

OBJECTIVE: Periodontitis is a chronic inflammatory periodontal disease resulting in destroyed periodontal tissue. Many studies have found that the host's inflammatory immune responses are involved in the risk of periodontal tissue damage. In this study, we aim to identify potential biomarkers and therapeutic targets related to immunity in periodontitis.

A personalized periodontitis risk based on nonimage electronic dental records by machine learning.

OBJECTIVE: This study aimed to develop a machine-learning (ML) model to predict the risk for Periodontal Disease (PD) based on nonimage electronic den...

A Fully Integrated Orthodontic Aligner With Force Sensing Ability for Machine Learning-Assisted Diagnosis.

Currently, the diagnosis of malocclusion is a highly demanding process involving complicated examinations of the dental occlusion, which increases the...

Explainable Deep Learning Approaches for Risk Screening of Periodontitis.

Several pieces of evidence have been reported regarding the association between periodontitis and systemic diseases. Despite the emphasized significan...

Unravelling integrated groundwater management in pollution-prone agricultural cities: A synergistic approach combining probabilistic risk, source apportionment and artificial intelligence.

Groundwater is vital for agricultural cities, but intensive farming and fertilizer use have increased contamination risks, particularly for non-carcin...

Training, use, and modifications related to artificial intelligence in postgraduate orthodontic programs in North America.

INTRODUCTION: The use of artificial intelligence (AI) is growing quickly and has already had a significant impact on the practice of orthodontics. Thi...

Automatic 3-dimensional quantification of orthodontically induced root resorption in cone-beam computed tomography images based on deep learning.

INTRODUCTION: Orthodontically induced root resorption (OIRR) is a common and undesirable consequence of orthodontic treatment. Traditionally, studies ...

Artificial intelligence for orthodontic diagnosis and treatment planning: A scoping review.

OBJECTIVES: To provide an overview of artificial intelligence (AI) applications in orthodontic diagnosis and treatment planning, and to evaluate wheth...

Segmentation of periapical lesions with automatic deep learning on panoramic radiographs: an artificial intelligence study.

Periapical periodontitis may manifest as a radiographic lesion radiographically. Periapical lesions are amongst the most common dental pathologies tha...

Enhancing local-scale groundwater quality predictions using advanced machine learning approaches.

Assessing groundwater quality typically involves labor-intensive, time-consuming, and costly laboratory tests, making real-time monitoring impractical...

Comparison of semi and fully automated artificial intelligence driven softwares and manual system for cephalometric analysis.

BACKGROUND: Cephalometric analysis has been used as one of the main tools for orthodontic diagnosis and treatment planning. The analysis can be perfor...

Deep learning method to automatically diagnose periodontal bone loss and periodontitis stage in dental panoramic radiograph.

OBJECTIVES: Artificial intelligence (AI) could be used as an automatically diagnosis method for dental disease due to its accuracy and efficiency. Thi...

Knowledge, attitude, and perception of orthodontic students, and orthodontists regarding role of artificial intelligence in field of orthodontics-An online cross-sectional survey.

BACKGROUND: Artificial intelligence (AI) is an emerging technology in orthodontics. The objective of this survey was to evaluate the knowledge, attitu...

Biomechanical simulation of segmented intrusion of a mandibular canine using Robot Orthodontic Measurement & Simulation System (ROSS).

OBJECTIVE: Aim of this study was to investigate the forces and moments during segmented intrusion of a mandibular canine using Cantilever-Intrusion-Sp...

Accuracy of deep learning-based upper airway segmentation.

INTRODUCTION: In orthodontic treatments, accurately assessing the upper airway volume and morphology is essential for proper diagnosis and planning. C...

Prediction of patient cooperation before orthodontic treatment: Handwriting and artificial intelligence.

BACKGROUND: The purpose of this study was to compare the success of various convolutional neural network (CNN) models trained with handwriting samples...

Exploiting Metal-Organic Frameworks for Vinylidene Fluoride Adsorption: From Force Field Development, Computational Screening to Machine Learning.

Metal-organic frameworks (MOFs) represent a distinctive class of nanoporous materials with considerable potential across a wide range of applications....

Utilization of an artificial intelligence-enhanced, web-based application to review bile duct brushing cytologic specimens: A pilot study.

BACKGROUND: The authors previously developed an artificial intelligence (AI) to assist cytologists in the evaluation of digital whole-slide images (WS...

Deciphering geochemical fingerprints and health implications of groundwater fluoride contamination in mica mining regions using machine learning tactics.

The contribution of mica mining activities to fluoride (F) contamination in groundwater has been chased in this study. For the purpose, groundwater sa...