OBJECTIVES: Evaluate the need for re-intervention on dental coronal restorations in adults seen in a network of general dental practitioners (ReCOL). MATERIALS AND METHODS: This observational, cross-sectional, multicenter study involved 40 practitio...
PURPOSE: To assess the knowledge, attitude and perception of dentists (dental students, dental school graduates/interns, postgraduate dentists) of the role of robotics (R) and artificial intelligence (AI) in oral health and preventive dentistry. The ...
BACKGROUND: Radiographic periodontal bone loss is one of the most important basis for periodontitis staging, with problems such as limited accuracy, inconsistency, and low efficiency in imaging diagnosis. Deep learning network may be a solution to im...
OBJECTIVES: Despite deep learning's wide adoption in dental artificial intelligence (AI) research, researchers from other dental fields and, more so, dental professionals may find it challenging to understand and interpret deep learning studies, thei...
Compendium of continuing education in dentistry (Jamesburg, N.J. : 1995)
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Dental artificial intelligence (AI) software can analyze and annotate radiographs in near real-time, transforming traditional gray-scale images into a color-coded diagnostic adjunct designed to draw the eye to potential pathologies. In this article, ...
Artificial intelligence (AI) is a division of computer science that allows machines to emulate human cognitive processes. In dentistry, AI is applied in clinical decision-making and can aid in detecting disease and predicting patterns based on existi...
OBJECTIVES: This study aimed to investigate the accuracy of deep learning algorithms to diagnose tooth caries and classify the extension and location of dental caries in cone beam computed tomography (CBCT) images. To the best of our knowledge, this ...