Acta Scientific Dental Sciences (ISSN: 2581-4893)

Review Article Volume 4 Issue 10

Dentistry and Artificial Intelligence

Rashmi J Kurup1*, Amandeep Sodhi2 and Sangeetha R3

1Post Graduate Student, Department of Oral Medicine and Radiology, Bangalore Institute of Dental Sciences and Hospital, Bangalore, India
2Reader, Department of Oral Medicine and Radiology, Bangalore Institute of Dental Sciences and Hospital, Bangalore, India
3Senior Lecturer, Department of Oral Medicine and Radiology, Bangalore Institute of Dental Sciences and Hospital, Bangalore, India

*Corresponding Author: Rashmi J Kurup, Post Graduate Student, Department of Oral Medicine and Radiology, Bangalore Institute of Dental Sciences and Hospital, Bangalore, India.

Received: July 27, 2020; Published: September 16, 2020

×

Abstract

 Artificial intelligence (AI) is a technology which is quickly advancing and has captivated the minds of researchers across the globe. The adoption of artificial intelligence (AI) in healthcare is developing while profoundly changing the face of healthcare delivery. AI is being employed in a horde of settings including hospitals, clinical laboratories and research facilities. From data processing and finding relevant information to using neural networks for diagnosis and to the introduction of augmented reality and virtual reality in dental education, its inception has witnessed some of the exceptional achievements in dentistry. The key applications involve diagnosis and treatment recommendations, patient engagement and adherence, and administrative activities. Thus, this circumstance demands every dentist to get acquainted with this technology as the future of dentistry is adjoining the execution of its applications. The need for proper documentation of the patient’s information, quick and dependable treatment protocols through robotics in the field of surgery has encouraged the utilization of these software technologies in assisting the dentist to diagnose and treat the patients productively. However, this technological advancement is still in the phases of outset and this article is an endeavor to highlight the role of artificial intelligence in dentistry

Keywords: Artificial Intelligence; Dentistry; Augmented Reality; Virtual Reality; Robotics; Surgery; Diagnosis and Treatment

×

References

  1. Vashisht Anu and Choudhary Ekta. “Artificial intelligence; mutating dentistry”. International Journal of Research and Analytical Reviews 1 (2019).
  2. Deshmukh Sonali Vijay. "Artificial intelligence in dentistry”. Journal of the International Clinical Dental Research Organization 2 (2018): 47.
  3. Mijwel Maad M. "History of artificial intelligence”. Computer Science, College of Science (2015): 1-6.
  4. Smith Chris., et al. “The history of artificial intelligence, University of Washington”. 8 (2006): 2017.
  5. Park Wook Joo and Jun-Beom Park. "History and application of artificial neural networks in dentistry”. European Journal of Dentistry 04 (2018): 594-601.
  6. Yaji Anisha S Prasad and A Pai. "Artificial intelligence in dento-maxillofacial radiology”. Acta Scientific Dental Sciences 3 (2019): 116-121.
  7. Khanna Sunali S and Prita A Dhaimade. "Artificial intelligence: Transforming dentistry today”. Indian Journal of Basic and Applied Medical Research 3 (2017): 161-167.
  8. Feeney L., et al. “A description of the new technologies used in transforming dental education”. British Dental Journal 1 (2008): 19-28.
  9. Lim K., et al. “Opportunistic screening for oral cancer and precancer in general dental practice: results of a demonstration study”. British Dental Journal9 (2003): 497-502.
  10. Rosmai Mohd Dom., et al. “The use of artificial intelligence to identify people at risk of oral cancer: empirical evidence in Malaysian University”. International Journal of Scientific Research in Education1 (2010): 10-20.
  11. Bas Burcu., et al. “Use of artificial neural network in differentiation of subgroups of temporomandibular internal derangements: a preliminary study”. Journal of oral and Maxillofacial Surgery1 (2012): 51-59.
  12. Krishna Ayinampudi Bhargavi., et al. “Role of artificial intelligence in diagnostic oral pathology-A modern approach”. Journal of Oral and Maxillofacial Pathology: JOMFP1 (2020): 152.
  13. Dar-Odeh Najla S., et al. “Predicting recurrent aphthous ulceration using genetic algorithms-optimized neural networks”. Advances and Applications in Bioinformatics and Chemistry: AABC 3 (2010): 7.
  14. Saghiri MA., et al. “A new approach for locating the minor apical foramen using an artificial neural network”. International Endodontic Journal3 (2012): 257-265.
  15. Kositbowornchai Suwadee., et al. “Performance of an artificial neural network for vertical root fracture detection: an ex vivo study”. Dental traumatology2 (2013): 151-155.
  16. Devito Karina Lopes., et al. “An artificial multilayer perceptron neural network for diagnosis of proximal dental caries”. Oral Surgery, Oral Medicine, Oral Pathology, Oral Radiology, and Endodontology6 (2008): 879-884.
  17. Bhan Anupama., et al. “Feature line profile based automatic detection of dental caries in bitewing radiography”. 2016 International Conference on Micro-Electronics and Telecommunication Engineering (ICMETE). IEEE (2016).
  18. Baliga M. "Artificial intelligence-The next frontier in pediatric dentistry”. Journal of the Indian Society of Pedodontics and Preventive Dentistry4 (2019): 315-315.
  19. Widmann G. "Image-guided surgery and medical robotics in the cranial area”. Biomedical Imaging and Intervention Journal1 (2007).
  20. Ruppin Jörg., et al. “Evaluation of the accuracy of three different computer‐aided surgery systems in dental implantology: optical tracking vs. stereolithographic splint systems”. Clinical Oral Implants Research7 (2008): 709-716.
  21. Patcas Raphael., et al. “Facial attractiveness of cleft patients: a direct comparison between artificial-intelligence-based scoring and conventional rater groups”. European Journal of Orthodontics4 (2019): 428-433.
  22. Xie Xiaoqiu., et al. “Artificial neural network modeling for deciding if extractions are necessary prior to orthodontic treatment”. The Angle Orthodontist2 (2010): 262-266.
  23. Birnbaum Nathan S and Heidi B Aaronson. "Dental impressions using 3D digital scanners: virtual becomes reality”. Compendium of Continuing Education in Dentistry 8 (2008): 494-496.
  24. Mackin N., et al. “Artificial intelligence in the dental surgery: an orthodontic expert system, a dental tool of tomorrow”. Dental Update8 (1991): 341.
  25. Li Peilin., et al. “Orthodontic treatment planning based on artificial neural networks”. Scientific Reports1 (2019): 1-9.
  26. Furman Elena., et al. “Virtual reality distraction for pain control during periodontal scaling and root planing procedures”. The Journal of the American Dental Association12 (2009): 1508-1516.
  27. Sohmura Taiji., et al. “CAD/CAM fabrication and clinical application of surgical template and bone model in oral implant surgery”. Clinical Oral Implants Research1 (2009): 87-93.
  28. Papantonopoulos G., et al. “Aggressive periodontitis defined by recursive partitioning analysis of immunologic factors”. Journal of Periodontology7 (2013): 974-984.
  29. Vera Vicente., et al. “Applying soft computing techniques to optimise a dental milling process”. Neurocomputing 109 (2013): 94-104.
  30. Vecsei Bálint., et al. “Comparison of the accuracy of direct and indirect three-dimensional digitizing processes for CAD/CAM systems–an In vitro study”. Journal of Prosthodontic Research2 (2017): 177-184.
  31. Kikuchi Hirono., et al. “Evaluation of a virtual reality simulation system for porcelain fused to metal crown preparation at Tokyo Medical and Dental University”. Journal of Dental Education6 (2013): 782-792.
  32. Vaishya Raju., et al. “Artificial Intelligence (AI) applications for COVID-19 pandemic”. Diabetes and Metabolic Syndrome: Clinical Research and Reviews (2020).
  33. Nagi Ravleen., et al. “Clinical applications and performance of intelligent systems in dental and maxillofacial radiology: A review”. Imaging Science in Dentistry2 (2020): 81.
  34. Chen Yo-Wei., et al. “Artificial intelligence in dentistry: Current applications and future perspectives”. Quintessence International 51 (2020): 248-257.
  35. Limonadi Farhad M., et al. “Design of an artificial neural network for diagnosis of facial pain syndromes”. Stereotactic and Functional Neurosurgery5-6 (2006): 212-220.
  36. McCartney Shirley., et al. “Use of an artificial neural network for diagnosis of facial pain syndromes: an update”. Stereotactic and Functional Neurosurgery1 (2014): 44-52.
  37. Xie Xiaoqiu., et al. “Artificial neural network modeling for deciding if extractions are necessary prior to orthodontic treatment”. The Angle Orthodontist2 (2010): 262-266.
  38. Miladinović Milan., et al. “Artificial intelligence in clinical medicine and dentistry”. Vojnosanitetski Pregled3 (2017): 267-272.
  39. Yang Yong-Hoon., et al. “Prediction of dental caries in 12-year-old children using machine-learning algorithms”. Journal of Korean Academy of Oral Health1 (2020): 55-63.
×

Citation

Citation: Rashmi J Kurup., et al. “Dentistry and Artificial Intelligence". Acta Scientific Dental Sciences 4.10 (2020): 26-32.




Metrics

Acceptance rate30%
Acceptance to publication20-30 days
Impact Factor1.278

Indexed In





News and Events


  • Certification for Review
    Acta Scientific certifies the Editors/reviewers for their review done towards the assigned articles of the respective journals.
  • Submission Timeline for Upcoming Issue
    The last date for submission of articles for regular Issues is December 25, 2024.
  • Publication Certificate
    Authors will be issued a "Publication Certificate" as a mark of appreciation for publishing their work.
  • Best Article of the Issue
    The Editors will elect one Best Article after each issue release. The authors of this article will be provided with a certificate of "Best Article of the Issue"

Contact US









ff

© 2024 Acta Scientific, All rights reserved.