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VOLUME 13 , ISSUE 2 ( July-December, 2021 ) > List of Articles


Artificial Intelligence in Dentistry: A Ray of Hope

Madhulika Banerjee

Keywords : Artificial intelligence, Artificial neural network, Augmented reality, COVID-19, Weak artificial intelligence

Citation Information : Banerjee M. Artificial Intelligence in Dentistry: A Ray of Hope. CODS J Dent 2021; 13 (2):58-60.

DOI: 10.5005/jp-journals-10063-0121

License: CC BY-NC 4.0

Published Online: 01-06-2022

Copyright Statement:  Copyright © 2021; The Author(s).


Artificial Intelligence (AI) is a technology which is rapidly growing. The Artificial Intelligence in healthcare system is developing with a very bright future. In dentistry, the key applications include diagnosis and treatment guidance, patient management as well as administrative activities. Thus, this AI system allows every dentist to get familiarize with this technology as the future of dentistry is going to be an amazing combination of this new magical innovation. The requirement for proper paperwork of the patient's information, quick and dependable treatment through robotics in the area of surgery has uplifted the utilization of these software technologies in assisting the dentist to diagnose and treat the patients practically and rewardingly. However, this technological advancement is still in the phases of early stage and this article is an attempt to spotlight the role of artificial intelligence in dentistry.

  1. Deshmukh SV. Artificial intelligence in dentistry. J Int Clin Dent Res Organ 2018;10(2):47–48. DOI: 10.4103/jicdro.jicdro_17_18
  2. Khanna SS, Dhaimade PA. Artificial intelligence: transforming dentistry today. Indian J Basic Appl Med Res 2017;6(3):161–167.
  3. Mijwel Maad M. History of artificial intelligence. 2015;1–6. DOI: 10.13140/RG.2.2.16418.15046
  4. Park WJ, Park JB. History and application of artificial neural networks in dentistry. Eur J Dent 2018;12(4):594–601. DOI: 10.4103/ejd.ejd_325_18
  5. Lavrač N. Selected techniques for data mining in medicine. Artif Intell Med 1999;16(1):3–23. DOI: 10.1016/s0933-3657(98)00062-1
  6. Lim K, Moles DR, Downer MC, et al. Opportunistic screening for oral cancer and precancer in general dental practice: results of a demonstration study. Br Dent J 2003;194(9):497–502. DOI: 10.1038/sj.bdj.4810069
  7. Al Haidan A, Abu-Hammad O, Dar-Odeh N. Predicting toothsurface loss using genetic algorithms-optimized artificial neural networks. Comput Math Methods Med 2014;2014:106236. DOI: 10.1155/2014/106236
  8. Alexander B, John S. Artificial intelligence in dentistry: current concepts and a peep into the future. Int J Adv Res 2018;6(12): 1105–1108. DOI: 10.21474/IJAR01/8242
  9. Baliga M. Artificial intelligence-the next frontier in pediatric dentistry. J Indian Soc Pedod Prev Dent 2019;37(4):315. DOI: 10.4103/JISPPD.JISPPD_319_19
  10. Furman E, Jasinevicius TR, Bissada NF, et al. Virtual reality distraction for pain control during periodontal scaling and root planing procedures. J Am Dent Assoc 2009;140(12):1508–1516. DOI: 10.14219/JADA.ARCHIVE.2009.0102
  11. Sohmura T, Kusumoto N, Otani T, et al. CAD/CAM fabrication and clinical application of surgical template and bone model in oral implant surgery. Clin Oral Implants Res 2009;20(1):87–93. DOI: 10.1111/j.1600-0501.2008.01588.x
  12. Papantonopoulos G, Takahashi K, Bountis T, et al. Aggressive periodontitis defined by recursive partitioning analysis of immunologic factors. J Periodontol 2013;84(7):974–984. DOI: 10.1371/journal.pone.0089757
  13. Widman G. Image guide surgery and medical robotics in cranial area. Biomed Imaging Interv J 2007;3(1):1–9. DOI: 10.2349/biij.3.1.e11
  14. Tan MS, Tan JW, Chang S-W, et al. A genetic programming approach to oral cancer prognosis. Peer J 2016;4:e2482. DOI: 10.7717/peerj.2482
  15. Bas B, Ozgonenel O, Ozden B, et al. Use of artificial neural network in differentiation of subgroups of temporomandibular internal derangements: a preliminary study. J Oral Maxillofac Surg 2012;70(1):51–59. DOI: 10.1016/j.joms.2011.03.069
  16. Hammond P, Davenport JC, Fitzpatrick FJ. Logic based constraints and design of dental prosthesis. Artif Intell Med 1993;5(5):431–446. DOI: 10.1016/0933-3657(93)90035-2
  17. Susic I, Travar M, Susic M. The application of CAD/CAM technology in dentistry. IOP Conf Series: Mater Sci Eng 2017;200:012020. DOI: 10.1088/1757-899X/200/1/012020
  18. Xie X, Wang L, Wang A. Artificial neural network modelling for deciding if extraction are necessary prior to orthodontic treatment. Angle Orthod 2010;80(2):262–266. DOI: 10.2319/111608-588.1
  19. Kattadiyil MT, Mursic Z, Al Rumaih H, et al. Intraoral scanning of hard and soft tissues for partial removable dental prosthesis fabrication. J Prosthet Dent 2014;112(3):444–448. DOI: 10.12691/ijdsr-8-1-2
  20. Saghiri MA, Asgar K, Boukani KK. A new approach for locating the minor apical foramen using an artificial neural network. Int Endod J 2012;45(3):257–265. DOI: 10.1111/j.1365-2591.2011.01970.x
  21. D Tandon, J Rajawat. Present and future of artificial intelligence in dentistry. J Oral Biol Craniofac Res 2020;10(4):391–396. DOI: 10.1016/j.jobcr.2020.07.015
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