Dental Health

Present status and future directions: Imaging techniques for the detection of periapical lesions.

Diagnosing and treating apical periodontitis (AP) in an attempt to preserve the natural dentition, and to prevent the direct and indirect systemic effects of this condition, is the major goal in endodontics. Considering that AP is frequently asymptomatic, and is most often associated with a lesion in the periapex of the affected tooth, within the maxillary bones, imaging becomes of paramount impor...

A Hierarchical Ensemble Deep Learning Activity Recognition Approach with Wearable Sensors Based on Focal Loss.

Abnormal activity in daily life is a relatively common symptom of chronic diseases, such as dementia. There will probably be a variety of repetitive activities in dementia patients' daily life, such as repeated handling of objects and repeated packing of clothes. It is particularly important to recognize the daily activities of the elderly, which can be further used to predict and monitor chronic ...

Automated analysis of three-dimensional CBCT images taken in natural head position that combines facial profile processing and multiple deep-learning models.

BACKGROUND AND OBJECTIVES: Analyzing three-dimensional cone beam computed tomography (CBCT) images has become an indispensable procedure for diagnosis...

iCVM: An Interpretable Deep Learning Model for CVM Assessment Under Label Uncertainty.

The Cervical Vertebral Maturation (CVM) method aims to determine the craniofacial skeletal maturational stage, which is crucial for orthodontic and or...

Systematic comparison of machine learning algorithms to develop and validate predictive models for periodontitis.

AIM: The aim of this study was to compare the validity of different machine learning algorithms to develop and validate predictive models for periodon...

Application of deep machine learning for the radiographic diagnosis of periodontitis.

OBJECTIVE: Successful application of deep machine learning could reduce time-consuming and labor-intensive clinical work of calculating the amount of ...

Deep learning in periodontology and oral implantology: A scoping review.

Deep learning (DL) has been employed for a wide range of tasks in dentistry. We aimed to systematically review studies employing DL for periodontal an...

Collaborative deep learning model for tooth segmentation and identification using panoramic radiographs.

Panoramic radiographs are an integral part of effective dental treatment planning, supporting dentists in identifying impacted teeth, infections, mali...

Age group prediction with panoramic radiomorphometric parameters using machine learning algorithms.

The aim of this study is to investigate the relationship of 18 radiomorphometric parameters of panoramic radiographs based on age, and to estimate the...

Deep Learning-Based Prediction of the 3D Postorthodontic Facial Changes.

With the increase of the adult orthodontic population, there is a need for an accurate and evidence-based prediction of the posttreatment face in 3 di...

Cephalometric Analysis in Orthodontics Using Artificial Intelligence-A Comprehensive Review.

Artificial intelligence (AI) is a branch of science concerned with developing programs and computers that can gather data, reason about it, and then t...

Accuracy and efficiency of automatic tooth segmentation in digital dental models using deep learning.

This study evaluates the accuracy and efficiency of automatic tooth segmentation in digital dental models using deep learning. We developed a dynamic ...

Accuracy of deep learning-based integrated tooth models by merging intraoral scans and CBCT scans for 3D evaluation of root position during orthodontic treatment.

OBJECTIVE: This study aimed to evaluate the accuracy of deep learning-based integrated tooth models (ITMs) by merging intraoral scans and cone-beam co...

Two-Stream Graph Convolutional Network for Intra-Oral Scanner Image Segmentation.

Precise segmentation of teeth from intra-oral scanner images is an essential task in computer-aided orthodontic surgical planning. The state-of-the-ar...

A two-stage deep learning architecture for radiographic staging of periodontal bone loss.

BACKGROUND: Radiographic periodontal bone loss is one of the most important basis for periodontitis staging, with problems such as limited accuracy, i...

Artificial Intelligence for Classifying and Archiving Orthodontic Images.

One of the main requirements for orthodontic treatment is continuous image acquisition. However, the conventional system of orthodontic image acquisit...

Inhibition of peptidyl arginine deiminase, a virulence factor, by antioxidant-rich : and evaluation.

, the cause of periodontitis, is also linked to many systemic disorders due to its citrullination capability from a unique peptidyl arginine deiminase...

Automatic detection of anteriorly displaced temporomandibular joint discs on magnetic resonance images using a deep learning algorithm.

OBJECTIVES: This study aimed to develop models that can automatically detect anterior disc displacement (ADD) of the temporomandibular joint (TMJ) on ...

Association of Gastroesophageal Reflux Disease with Preterm Birth: Machine Learning Analysis.

BACKGROUND: This study used machine learning and population data for testing the associations of preterm birth with gastroesophageal reflux disease (G...

Complexity and data mining in dental research: A network medicine perspective on interceptive orthodontics.

Procedures and models of computerized data analysis are becoming researchers' and practitioners' thinking partners by transforming the reasoning under...