Applications of artificial intelligence in dentistry: A comprehensive review

Abstract

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 different advances that these technologies and tools have produced, paying special attention to the area of esthetic dentistry and color research. Materials and methods The comprehensive review was conducted in MEDLINE/PubMed, Web of Science, and Scopus databases, for papers published in English language in the last 20 years. Results Out of 3871 eligible papers, 120 were included for final appraisal. Study methodologies included deep learning (DL; n = 76), fuzzy logic (FL; n = 12), and other ML techniques (n = 32), which were mainly applied to disease identification, image segmentation, image correction, and biomimetic color analysis and modeling. Conclusions The insight provided by the present work has reported outstanding results in the design of high‐performance decision support systems for the aforementioned areas. The future of digital dentistry goes through the design of integrated approaches providing personalized treatments to patients. In addition, esthetic dentistry can benefit from those advances by developing models allowing a complete characterization of tooth color, enhancing the accuracy of dental restorations. Clinical significance The use of AI and ML has an increasing impact on the dental profession and is complementing the development of digital technologies and tools, with a wide application in treatment planning and esthetic dentistry procedures.

Where Is the Artificial Intelligence Applied in Dentistry? Systematic Review and Literature Analysis

“…The prevention of oral diseases based on AI impacts on oral hygiene behavior has also been reported. A novel method, based on wrist-worn inertial sensors to detect brushing and flossing behaviors, was proposed [ 7 , 122 , 123 ].…”

“…To understand the current and future clinical AI utilizations in dentistry, we must first comprehend the elemental AI technologies. Figure 2 represents the relationship between the various technologies [ 6 , 7 , 8 , 9 ]. AI connotes fundamental technologies including machine learning, artificial neural networks (ANN), and deep learning.…”

“…For clinical AI applications in dentistry, a full digital workflow transformation is necessary [ 16 , 17 , 18 , 19 , 20 , 21 ]. Currently, various examples of advanced dental technologies can be found based on digital workflows [ 7 , 16 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 ]. Their goal is to enhance the efficiency and quality of delivered services.…”

“…After refinement of the results, only eight were comparable to this paper with comprehensive focus on dentistry including literature analysis, although these were either missing trend analysis or had a scope of no longer than 2 years. Of these eight reviews only two were registered in SCOPUS/Web of Science [ 7 , 60 ].…”

“…Only six were reviews fully overlapping with the Web of Science query results. However, there was one interesting comprehensive review by Carrillo-Perez et al [ 7 ]. This study was published in January 2022, although with early access in November 2021, and it was indexed in Web of Science in December 2021, which explains why it was not provided as a result of the original query for Web of Science 2022 publications.…”