Application of Artificial Intelligence in Dentistry
DOI:
https://doi.org/10.56294/hl2024.454Keywords:
Dentistry, Artificial Intelligence, Machine Learning, Advantages, ChallengesAbstract
Dentistry is one of the youngest medical applications of artificial intelligence. Here, artificial intelligence and its various components (machine learning, deep learning, neural networks) are applied at a number of stages, such as diagnosis, decision-making, treatment planning, and prediction.
Dental radiology, maxillofacial surgery, orthopedic dentistry is some of the application areas of artificial intelligence in dentistry. Despite some advantages, there are a number of problems (security, legal and ethical problems during decision-making, etc.). Their solution is also related to the development of artificial intelligence application. This updates and improves its future application directions.
In the article, the application, management, advantages, application problems, and future directions of artificial intelligence in dentistry are mentioned.
Keywords: Dentistry, Artificial Intelligence, Machine Learning, Advantages, Challenges.
References
1. A. K. Anand, R. K. Mahto, and A. Prasad, “Analysis of Cyberbullying Behaviors Using Machine Learning:A Study on Text Classification,” LatIA, vol. 3, pp. 126–126, Jan. 2025, doi: 10.62486/latia2023126.
7. T. Shan, F. Tay, and L. Gu, “Application of Artificial Intelligence in Dentistry,” Journal of Dental Research, vol. 100, pp. 232–244, Oct. 2020, doi: 10.1177/0022034520969115.
8. T. Kishimoto, T. Goto, T. Matsuda, Y. Iwawaki, and T. Ichikawa, “Application of artificial intelligence in the dental field: A literature review.,” Journal of prosthodontic research, Jan. 2021, doi: 10.2186/jpr.JPR_D_20_00139.
9. A. Khang, V. A. Hajimahmud, A. V. Alyar, M. K. Etibar, V. A. Soltanaga, and Y. Niu, “Application of industrial robotics in manufacturing,” in Machine Vision and Industrial Robotics in Manufact.: Approaches, Technologies, and Applic., CRC Press, 2024, pp. 85–100. doi: 10.1201/9781003438137-5.
13. F. Tabatabaian, S. Vora, and S. Mirabbasi, “Applications, functions, and accuracy of artificial intelligence in restorative dentistry: A literature review.,” Journal of esthetic and restorative dentistry : official publication of the American Academy of Esthetic Dentistry ... et al.., Jul. 2023, doi: 10.1111/jerd.13079.
14. C. Mörch et al., “Artificial Intelligence and Ethics in Dentistry: A Scoping Review,” Journal of Dental Research, vol. 100, pp. 1452–1460, Jun. 2021, doi: 10.1177/00220345211013808.
15. F. Schwendicke et al., “Artificial Intelligence for dentistry: FDI ARTIFICIAL IN℡LIGENCE WORKING GROUP”.” Online.. Available: www.fdiworlddental.org
16. D. Hao, W. Jiamin, Z. Wuyuan, M. J. P., B. M. F., and T. J. K. H, “Artificial intelligence in dentistry—A review,” Frontiers in Dental Medicine, vol. VOLUME=4, 2023, doi: 10.3389/fdmed.2023.1085251.
17. A. Ossowska, A. Kusiak, and D. Świetlik, “Artificial Intelligence in Dentistry—Narrative Review,” International Journal of Environmental Research and Public Health, vol. 19, Mar. 2022, doi: 10.3390/ijerph19063449.
18. F. Schwendicke, W. Samek, and J. Krois, “Artificial Intelligence in Dentistry: Chances and Challenges,” Journal of Dental Research, vol. 99, pp. 769–774, Apr. 2020, doi: 10.1177/0022034520915714.
19. K. Dhingra, “Artificial intelligence in dentistry: current state and future directions,” The Bulletin of the Royal College of Surgeons of England, vol. 105, no. 8, pp. 380–383, 2023.
20. M. Vodanović, M. Subašić, D. Milošević, and S. Pavičin, “Artificial Intelligence in Medicine and Dentistry,” Acta Stomatologica Croatica, vol. 57, pp. 70–84, Mar. 2023, doi: 10.15644/asc57/1/8.
21. I. Al-Barazanchi et al., “Blockchain-Technology-Based Solutions for IOT Security,” Iraqi. J. Comput. Sci. Math., vol. 3, no. 1, pp. 53–63, 2022, doi: 10.52866/ijcsm.2022.01.01.006.
24. T. Bonny, W. A. Nassan, K. Obaideen, M. N. A. Mallahi, Y. Mohammad, and H. El-Damanhoury, “Contemporary Role and Applications of Artificial Intelligence in Dentistry,” F1000Research, vol. 12, Sep. 2023, doi: 10.12688/f1000research.140204.1.
25. F. Schwendicke, T. Golla, M. Dreher, and J. Krois, “Convolutional neural networks for dental image diagnostics: A scoping review,” Journal of Dentistry.103226, 2019.
28. F. Schwendicke et al., Deep learning for cephalometric landmark detection: Systematic review and meta-analysis. Clin Oral Investig, 2021.
29. J. Grischke, L. Johannsmeier, L. Eich, L. Griga, and S. Haddadin, “Dentronics: Towards robotics and artificial intelligence in dentistry.,” Dental materials : official publication of the Academy of Dental Materials, Apr. 2020, doi: 10.1016/j.dental.2020.03.021.
30. Z. Khurshid, “Digital Dentistry: Transformation of Oral Health and Dental Education with Technology,” Eur J Dent, vol. Oct;17(4):943-944, 2023, doi: 10.1055/s-0043-1772674.
31. Z. M. Semerci and S. Yardımcı, “Empowering Modern Dentistry: The Impact of Artificial Intelligence on Patient Care and Clinical Decision Making,” Diagnostics, vol. 14, p. 1260, 2024, doi: 10.3390/diagnostics14121260.
40. I. Al-Barazanchi et al., “Proposed New Framework Scheme for Path Loss in Wireless Body Area Network,” Iraqi. J. Comput. Sci. Math., vol. 3, no. 1, pp. 11–21, 2022, doi: 10.52866/ijcsm.2022.01.01.002.
42. S. A. Alowais, S. S. Alghamdi, and N. Alsuhebany, “Revolutionizing healthcare: the role of artificial intelligence in clinical practice,” BMC Med Educ, vol. 23, p. 689, 2023, doi: 10.1186/s12909-023-04698-z.
43. H. R. Penubadi et al., “Sustainable electronic document security: a comprehensive framework integrating encryption, digital signature and watermarking algorithms,” Herit. Sustain. Dev., vol. 5, no. 2, pp. 391–404, 2023, doi: 10.37868/hsd.v5i2.359.
44. H. R. Abdulshaheed et al., “Sustainable optimizing WMN performance through meta-heuristic TDMA link scheduling and routing,” Herit. Sustain. Dev., vol. 6, no. 1, pp. 111–126, 2024, doi: 10.37868/hsd.v6i1.389.
46. A. Khang et al., “The Landscape and Prospects of AI-Driven Applications in the Era of Digital Economy,” in Revolutionizing the AI-Digital Landsc.: A Guide to Sustainable Emerg. Technologies for Marketing Professionals, Taylor and Francis, 2024, pp. 1–14. doi: 10.4324/9781032688305-1.
47. Falk Schwendicke, Markus Blatz, Sergio Uribe, William Cheung, Mahesh Verma, Jina Linton, and Young Jun Kim, “Artificial Intelligence for dentistry: FDI ARTIFICIAL INTELLIGENCE WORKING GROUP”, WHITE PAPER, www.fdiworlddental.org
48. Schwendicke F, Chaurasia A, Arsiwala L, Lee JH, Elhennawy K, Jost-Brinkmann PG, Demarco F, Krois J. 2021a. Deep learning for cephalometric landmark detection: Systematic review and meta-analysis. Clin Oral Investig
49. Schwendicke F, Golla T, Dreher M, Krois J. 2019. Convolutional neural networks for dental image diagnostics: A scoping review. Journal of Dentistry.103226.
50. URL: https://pocketdentistry.com/6-treatment-planning/
51. Semerci, Z.M.; Yardımcı, S. Empowering Modern Dentistry: The Impact of Artificial Intelligence on Patient Care and Clinical Decision Making. Diagnostics 2024, 14, 1260. https://doi.org/10.3390/diagnostics14121260
52. Khurshid Z. Digital Dentistry: Transformation of Oral Health and Dental Education with Technology. Eur J Dent. 2023 Oct;17(4):943-944. doi: 10.1055/s-0043-1772674. Epub 2023 Sep 20. PMID: 37729928; PMCID: PMC10756720.
53. Ding Hao, Wu Jiamin, Zhao Wuyuan, Matinlinna Jukka P., Burrow Michael F., Tsoi James K. H., "Artificial intelligence in dentistry—A review” Frontiers in Dental Medicine, VOLUME=4, 2023, URL=https://www.frontiersin.org/journals/dental-medicine/articles/10.3389/fdmed.2023.1085251
54. Alowais, S.A., Alghamdi, S.S., Alsuhebany, N. et al. Revolutionizing healthcare: the role of artificial intelligence in clinical practice. BMC Med Educ 23, 689 (2023). https://doi.org/10.1186/s12909-023-04698-z
55. Dhingra, K. "Artificial intelligence in dentistry: current state and future directions." The Bulletin of the Royal College of Surgeons of England 105.8 (2023): 380-383.
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Copyright (c) 2024 Nazila Ragimova , Vugar Abdullayev , Ayan Mirzoyeva , Elnare Mirzoyeva (Author)
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