Introduction Deep learning methods have recently been applied for the processing of
medical images, and they have shown promise in a variety of applications. This study aimed …

Background and aim Artificial intelligence (AI) technology has been increasingly developed
in oral and maxillofacial imaging. The aim of this systematic review was to assess the …

Aim: Deep learning algorithms have lately been used for medical image processing, and
they have showed promise in a range of applications. The purpose of this study was to …

Background and Objectives: We aimed to develop a predictive model for the outcome of
bruxism treatments using ultrasonography (USG)-based machine learning (ML) techniques …

Objectives: The purpose of this study was to evaluate the effectiveness of dental caries
segmentation on the panoramic radiographs taken from children in primary dentition, mixed …

Everyone has or will have experienced some degree of neck pain. Typically, neck pain is
associated with the sensation of tense, tight, or stiff neck muscles. However, it is unclear …

Artificial intelligence (AI) holds the potential to revolutionize the field of dentistry by
enhancing diagnosis, treatment planning, and patient outcomes. AI's future applications …

Introductions: Radiographic image segmentation is a process that aims to distinguish the
voxels and pixels within a de ned area of interest from the background, which is vital for …

Objective: In this study, we aimed to evaluate the success of the last three versions of YOLO
algorithms, YOLOv5, YOLOv7 and YOLOv8, with segmentation feature in the segmentation …

Aim: The objective of this study is to utilize artificial intelligence for the segmentation of
masticatory muscles in ultrasound images. Materials and Methods: The study comprised a …