This work was funded by the Spanish Ministry of Sciences, Innovation and Universities under Projects RTI2018-101674-B-I00 and PGC2018-101904-A-100, University of Granada project A.TEP. 280.UGR18, I+D+I Junta de Andalucia 2020 project P20-00200, and Fapergs/Capes do Brasil grant 19/25510000928-3. Funding for open-access charge: Universidad de Granada/CBUAObjective: 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.Spanish Ministry of Sciences, Innovation and Universities RTI2018-101674-B-I00
PGC2018-101904-A-100University of Granada project A.TEP. 280.UGR18Junta de Andalucia P20-00200Fapergs/Capes do Brasil grant 19/25510000928-3Universidad de Granada/CBU
