BACKGROUND: Effective patient education is critical in enhancing treatment outcomes and reducing anxiety in dental procedures. This study compares the effectiveness of AI-generated educational materials with traditional methods in improving patient c...
OBJECTIVES: Intraoral photographs might be considered the machine-readable equivalent of a clinical-based visual examination and can potentially be used to detect and categorize dental restorations. The first objective of this study was to develop a ...
OBJECTIVES: We aimed to understand how artificial intelligence (AI) influences dentists by comparing their gaze behavior when using versus not using an AI software to detect primary proximal carious lesions on bitewing radiographs.
Artificial intelligence (AI) is increasingly prevalent in biomedical and industrial development, capturing the interest of dental professionals and patients. Its potential to improve the accuracy and speed of dental procedures is set to revolutionize...
OBJECTIVES: This study aims to explore and discuss recent advancements in tooth reconstruction utilizing deep learning (DL) techniques. A review on new DL methodologies in partial and full tooth reconstruction is conducted.
Quintessence international (Berlin, Germany : 1985)
38847140
OBJECTIVE: Artificial intelligence (AI) applications in restorative dentistry have remarkably increased in the past 5 years. This review outlines the applications, promises, and limitations of AI in the most performed procedures in restorative dentis...
The journal of evidence-based dental practice
39631965
ARTICLE TITLE AND BIBLIOGRAPHIC INFORMATION: Shetty, S., et al. (2023). "Artificial intelligence systems in dental shade-matching: A systematic review." J Prosthodont. DOI: 10.1111/jopr.13805.
PURPOSE AND OBJECTIVE: Objective, valid, and reliable evaluations are needed in order to develop haptic skills in dental education. The aim of this study is to investigate the validity and reliability of the machine learning method in evaluating the ...
OBJECTIVES: Deep learning has revolutionized image analysis for dentistry. Automated segmentation of dental radiographs is of great importance towards digital dentistry. The performance of deep learning models heavily relies on the quality and divers...