Objective To perform a comprehensive review of the use of artificial intelligence (AI) and
machine learning (ML) in dentistry, providing the community with a broad insight on the …

Machine learning (ML) is being increasingly employed in dental research and application.
We aimed to systematically compile studies using ML in dentistry and assess their …

Background: Machine learning (ML) has emerged as a branch of artificial intelligence
dealing with the analysis of large amounts of data. The applications of ML algorithms have …

Objectives Artificial intelligence (AI) is an emerging field in dentistry. AI is gradually being
integrated into dentistry to improve clinical dental practice. The aims of this sco** review …

The Wasserstein distance is a powerful metric based on the theory of optimal mass
transport. It gives a natural measure of the distance between two distributions with a wide …

ABSTRACT PURPOSE The purpose of this work was to develop a knowledge-based dose
prediction system using a convolution neural network (CNN) for cervical brachytherapy …

Background and purpose Computed tomography (CT) is one of the most common medical
imaging modalities in radiation oncology and radiomics research, the computational voxel …

Quality assurance of data prior to use in automated pipelines and image analysis would
assist in safeguarding against biases and incorrect interpretation of results. Automation of …

Purpose We conducted our study to develop a tool capable of automatically detecting dental
artifacts in a CT scan on a slice-by-slice basis and to assess the dosimetric impact of …

Cone Beam Computed Tomography (CBCT) is widely used in dentistry for diagnostics and
treatment planning. CBCT Imaging has a long acquisition time and consequently, the patient …