Objectives To conduct a scoping review focusing on artificial intelligence (AI) applications in
presurgical dental implant planning. Additionally, to assess the automation degree of …

Background In the past, dentistry heavily relied on manual image analysis and diagnostic
procedures, which could be time-consuming and prone to human error. The advent of …

Objectives To train and validate a cloud-based convolutional neural network (CNN) model
for automated segmentation (AS) of dental implant and attached prosthetic crown on cone …

Objectives To develop and assess the performance of a novel artificial intelligence (AI)‐
driven convolutional neural network (CNN)‐based tool for automated three‐dimensional …

The process of creating virtual models of dentomaxillofacial structures through three-
dimensional segmentation is a crucial component of most digital dental workflows. This …

Objectives To assess the performance, time-efficiency, and consistency of a convolutional
neural network (CNN) based automated approach for integrated segmentation of …

Background The purpose of this study was to compare the segmentation performances of
the 2D, 2.5 D, and 3D networks for maxillary sinuses (MSs) and lesions inside the maxillary …

Background There are different values reported about the performance of artificial
intelligence using cone-beam computed tomography (CBCT) for segmentation of oral and …

Statement of problem The use of artificial intelligence (AI) in dentistry has grown. However,
the accuracy of clinical applications in implant dentistry is still unclear. Purpose The purpose …

Background: The aim of our study is to provide successful automatic segmentation of various
objects on orthopantomographs (OPGs). Methods: 8138 OPGs obtained from the archives of …