Artificial intelligence applications in dentistry: A scoping review
Code: G-1791
Authors: Parham Farzam * ℗
Schedule: Not Scheduled!
Tag: Clinical Decision Support System
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Abstract:
Abstract
Background and aims: This review aims to provide a scopped overview of the applications of artificial intelligence (AI) and machine learning (ML) in the field of dentistry, offering the professional community an in-depth understanding of the advancements enabled by these technologies. Particular emphasis is placed on their contributions to esthetic dentistry and color science. Materials and methods: The scoping review was conducted through Cochrane, PubMed, Web of Science, and Scopus databases, for eligible articles published in the last 5 years. Results: From a total of 3,871 eligible articles, 120 were selected for final evaluation. The methodologies employed across these studies included deep learning (DL; n = 76), fuzzy logic (FL; n = 12), and other ML techniques (n = 32). These approaches were primarily utilized for disease identification, image segmentation, image enhancement, and biomimetic color analysis and modeling. Conclusions: The findings presented in this study highlight significant advancements in the development of high-performance decision support systems across the aforementioned domains. The future of digital dentistry lies in the creation of integrated approaches that enable personalized patient care. Moreover, esthetic dentistry stands to benefit substantially from these innovations through the development of advanced models for comprehensive tooth color characterization, thereby improving the precision of dental restorations. Clinical Significance: The integration of AI and ML is exerting a growing influence on the dental profession, complementing the advancement of digital technologies and tools. These innovations are being widely applied in treatment planning as well as in various esthetic dentistry procedures.
Keywords
Artificial Intelligence, Deep Learning, Dentistry, Machine
