OBJECTIVE: This study aims to investigate the effect of number of data on model performance, for the detection of tooth numbering problem on dental panoramic radiographs, with the help of image processing and deep learning algorithms.
OBJECTIVE: Federated Learning (FL) enables collaborative training of artificial intelligence (AI) models from multiple data sources without directly sharing data. Due to the large amount of sensitive data in dentistry, FL may be particularly relevant...
OBJECTIVES: Lingual mandibular bone depression (LMBD) is a developmental bony defect in the lingual aspect of the mandible that does not require any surgical treatment. It is sometimes confused with a cyst or another radiolucent pathologic lesion on ...
International journal of legal medicine
Apr 14, 2023
Dental radiographies have been used for many decades for estimating the chronological age, with a view to forensic identification, migration flow control, or assessment of dental development, among others. This study aims to analyse the current appli...
Oral surgery, oral medicine, oral pathology and oral radiology
Mar 30, 2023
OBJECTIVES: We aimed to develop an artificial intelligence-based clinical dental decision-support system using deep-learning methods to reduce diagnostic interpretation error and time and increase the effectiveness of dental treatment and classificat...
This study aimed to evaluate the accuracy of automated deep learning (DL) algorithm for identifying and classifying various types of dental implant systems (DIS) using a large-scale multicenter dataset. Dental implant radiographs of pos-implant surge...
BACKGROUND: Dental age (DA) estimation using two convolutional neural networks (CNNs), VGG16 and ResNet101, remains unexplored. In this study, we aimed to investigate the possibility of using artificial intelligence-based methods in an eastern Chines...
OBJECTIVES: A separated endodontic instrument is one of the challenging complications of root canal treatment. The purpose of this study was to compare two deep learning methods that are convolutional neural network (CNN) and long short-term memory (...