Teeth-based age and sex estimation is an important task in mass disasters, criminal scenes, and archeology. Although various methods have been proposed, most of them are subjective and influenced by observers' experiences. In this study, we aimed to ...
This study aimed to develop an artificial intelligence (AI) model using deep learning techniques to diagnose dens evaginatus (DE) on periapical radiography (PA) and compare its performance with endodontist evaluations. In total, 402 PA images (138 DE...
OBJECTIVE(S): This study aims to evaluate the influence of the piezocision surgery in the orthodontic biomechanics, as well as in the magnitude and direction of tooth movement in the mandibular arch using novel artificial intelligence (AI)-automated ...
There has been a significant increase in robot-assisted dental procedures in the past decade, particularly in the area of robot-assisted implant placement. The objective of this case report was to assess the initial use of the Yomi Robot's assistance...
OBJECTIVE: To examine the patterns of pretreatment facial soft tissue shape in orthodontic cases with premolar extraction using artificial intelligence (AI) and to investigate the corresponding changes.
OBJECTIVE: The aim of this study was to evaluate the accuracy of a combined approach based on an isotopological remeshing and statistical shape analysis (SSA) to capture key anatomical features of altered and intact premolars. Additionally, the study...
Fiber posts present significant challenges for nonsurgical endodontic retreatment, as improper removal may result in iatrogenic root perforation or even root fracture. Recently, robotic technology has attracted considerable attention in dentistry and...
BACKGROUND: Hypodontia is the absence of one or more teeth in the primary or permanent dentition during development, and radiographic imaging is the most common method of diagnosis. However, in recent years, artificial intelligence-based decision sup...
To develop and validate an artificial intelligence (AI)-driven tool for the automatic segmentation of pulp cavity structures in maxillary premolars teeth on cone-beam computed tomography (CBCT). One hundred and eleven CBCT scans were divided into tra...
BACKGROUND: The aim of our study was to develop and evaluate a deep learning model (BiStageNet) for automatic detection of dens evaginatus (DE) premolars on orthodontic intraoral photographs. Additionally, based on the training results, we developed ...