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 …

Flexible and miniaturized devices inspired by the advances in electronic materials,
fabrication technologies, and wireless communication have emerged as the next‐generation …

Introduction Tooth segmentation on cone-beam computed tomographic (CBCT) imaging is a
labor-intensive task considering the limited contrast resolution and potential disturbance by …

Accurate segmentation of the jaw (ie, mandible and maxilla) and the teeth in cone beam
computed tomography (CBCT) scans is essential for orthodontic diagnosis and treatment …

Artificial intelligence has been widely used in the field of dentistry in recent years. The
present study highlights current advances and limitations in integrating artificial intelligence …

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 …

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

Objective Tooth segmentation and classification from cone-beam computed tomography
(CBCT) is a prerequisite for diagnosis and treatment planning in the majority of digital dental …

Background Ultrasound is a non-invasive, cross-sectional imaging technique emerging in
dentistry. It is an adjunct tool for diagnosing pathologies in the oral cavity that overcomes …

Early detection and prediction of bio-tribocorrosion can avert unexpected damage that may
lead to secondary revision surgery and associated risks of implantable devices. Therefore …