BACKGROUND: This study introduces a novel deep learning methodology for the automated detection of a wide range of dental prostheses, including crowns, bridges, and implants, as well as various dental treatments such as fillings, root canal therapies...
OBJECTIVE: The integration of artificial intelligence (AI) into CAD/CAM workflows has revolutionized dental prosthetics manufacturing, yet its morphological trueness compared to manual design remains underexplored.
OBJECTIVES: Accurate tooth numbering and restoration detection on periapical radiographs in mixed dentition are critical to the treatment planning process. They also improve the speed and accuracy of treatment processes by automating the early diagno...
BACKGROUND: Accurate restoration and reconstruction of tooth morphology are crucial in restorative dentistry, implantology, and forensic odontology. Traditional methods, like manual wax modeling and template-based computer-aided design (CAD), struggl...
OBJECTIVE: Dental electronic health records (EHRs) often lack comprehensive data for evaluating procedure outcomes. Machine learning (ML) enables predictive modeling but its applicability to dental EHR data remains unclear. This study assessed the re...
Journal of esthetic and restorative dentistry : official publication of the American Academy of Esthetic Dentistry ... [et al.]
Mar 28, 2025
OBJECTIVES: This study aimed to assess the influence of background color, ceramic shade, translucency, and thickness on the color matching of lithium disilicate restorations and to use a neural network model to predict the optimal parameters for shad...
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...
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 ...
The journal of evidence-based dental practice
Sep 17, 2024
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.
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