Download PDF
CC BY 4.0 · Eur J Dent 2023; 17(03): 567-568
DOI: 10.1055/s-0043-1770913
Editorial

Embracing the Unprecedented Pace of Change: Artificial Intelligence's Impact on Dentistry and Beyond

Hakan Turkkahraman 
1   Department of Orthodontics and Oral Facial Genetics, School of Dentistry, Indiana University, Indianapolis, Indiana, United States
› Author Affiliations
› Further Information
Also available at
   Permissions and Reprints

Introduction

Human beings have long exhibited a natural fear of the unknown. We tend to initially ignore novel changes, only to gradually adapt to them as they become familiar. However, the recent emergence of generative artificial intelligence (AI) applications has propelled us into an era of technological advancement comparable to the invention of electricity. The remarkable speed of these developments has caught many off guard, surpassing our expectations. It is not the change itself that instills fear but rather the breathtaking pace at which it unfolds. The challenge lies in ensuring that regulations keep pace with technological advancements to guide the responsible use of AI. In this guest editorial, we explore the transformative potential of AI in dentistry and emphasize the need to embrace change while maintaining ethical frameworks.



Publication History

Article published online:
20 July 2023

© 2023. rThe Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

Thieme Medical and Scientific Publishers Pvt. Ltd.
A-12, 2nd Floor, Sector 2, Noida-201301 UP, India

 

  • References

  • 1 Mertens S, Krois J, Cantu AG, Arsiwala LT, Schwendicke F. Artificial intelligence for caries detection: randomized trial. J Dent 2021; 115: 103849
    CrossrefPubMedSearch in Google Scholar
  • 2 Zhou X, Yu G, Yin Q, Liu Y, Zhang Z, Sun J. Context aware convolutional neural network for children caries diagnosis on dental panoramic radiographs. Comput Math Methods Med 2022; 2022: 6029245
    CrossrefPubMedSearch in Google Scholar
  • 3 Schwendicke F, Cejudo Grano de Oro J, Garcia Cantu A, Meyer-Lueckel H, Chaurasia A, Krois J. Artificial intelligence for caries detection: value of data and information. J Dent Res 2022; 101 (11) 1350-1356
    CrossrefPubMedSearch in Google Scholar
  • 4 Lee KS, Kwak HJ, Oh JM. et al. Automated detection of TMJ osteoarthritis based on artificial intelligence. J Dent Res 2020; 99 (12) 1363-1367
    CrossrefPubMedSearch in Google Scholar
  • 5 Mason T, Kelly KM, Eckert G, Dean JA, Dundar MM, Turkkahraman H. A machine learning model for orthodontic extraction/non-extraction decision in a racially and ethnically diverse patient population. Int Orthod 2023; 21 (03) 100759
    CrossrefPubMedSearch in Google Scholar
  • 6 Lee H, Ahmad S, Frazier M, Dundar MM, Turkkahraman H. A novel machine learning model for class III surgery decision. J Orofac Orthop 2022
    CrossrefPubMedSearch in Google Scholar
  • 7 Leavitt L, Volovic J, Steinhauer L. et al. Can we predict orthodontic extraction patterns by using machine learning?. Orthod Craniofac Res 2023
    CrossrefPubMedSearch in Google Scholar
  • 8 Mureșanu S, Almășan O, Hedeșiu M, Dioșan L, Dinu C, Jacobs R. Artificial intelligence models for clinical usage in dentistry with a focus on dentomaxillofacial CBCT: a systematic review. Oral Radiol 2023; 39 (01) 18-40
    CrossrefPubMedSearch in Google Scholar
  • 9 Wood T, Anigbo JO, Eckert G, Stewart KT, Dundar MM, Turkkahraman H. Prediction of the post-pubertal mandibular length and y axis of growth by using various machine learning techniques: a retrospective longitudinal study. Diagnostics (Basel) 2023; 13 (09) 1553
    CrossrefPubMedSearch in Google Scholar
  • 10 Mahrous A, Botsko DL, Elgreatly A, Tsujimoto A, Qian F, Schneider GB. The use of artificial intelligence and game-based learning in removable partial denture design: a comparative study. J Dent Educ 2023
    PubMedSearch in Google Scholar
  • 11 Islam NM, Laughter L, Sadid-Zadeh R. et al. Adopting artificial intelligence in dental education: a model for academic leadership and innovation. J Dent Educ 2022; 86 (11) 1545-1551
    CrossrefPubMedSearch in Google Scholar
  • 12 Imran E, Adanir N, Khurshid Z. Significance of haptic and virtual reality simulation (VRS) in the dental education: a review of literature. Appl Sci (Basel) 2021; 11 (21) 10196
    CrossrefSearch in Google Scholar