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The Role of Artificial Intelligence in Orthodontic Treatment

Year 2023, Volume: 25 Issue: 2, 340 - 346, 31.08.2023
https://doi.org/10.24938/kutfd.1335382

Abstract

Artificial intelligence, is generally considered one of the most transformative technologies of the 21st century. One of the fields in which artificial intelligence is increasingly being integrated is healthcare services. Within this broad scope, a particular discipline that is starting to witness the profound impacts of artificial intelligence is orthodontics. The purpose of this review is to encourage further discussion on the integration of artificial intelligence in orthodontics and to focus on its potential to transform and enhance this field by bringing increased accuracy, efficiency, and personalization to patient care.

Project Number

yok

References

  • Ishii E, Ebner DK, Kimura S, Agha-Mir-Salim L, Uchimido R, Celi LA. The advent of medical artificial intelligence: lessons from the Japanese approach. J Intensive Care. 2020;8:35.
  • Chen H, Chen S, Zhao J. Integrated design of financial self-service terminal based on artificial intelligence voice ınteraction. Front Psychol. 2022;13:850092.
  • Theodosiou AA, Read RC. Artificial intelligence, machine learning and deep learning: Potential resources for the infection clinician. J Infect. 2023:S0163-4453(23)00379-1.
  • Jiang F, Jiang Y, Zhi H, Dong Y, Li H, Ma S, et al. Artificial intelligence in healthcare: Past, present and future. Stroke Vasc Neurol. 2017;2(4):230-43.
  • Liu J, Chen Y, Li S, Zhao Z, Wu Z. Machine learning in orthodontics: Challenges and perspectives. Adv Clin Exp Med. 2021;30(10):1065-74.
  • Israni ST, Verghese A.  Humanizing artificial intelligence. JAMA. 2019;321(1):29-30.
  • Ghafari JG. Centennial inventory: the changing face of orthodontics. Am J Orthod Dentofacial Orthop. 2015;148(5):732-9.
  • Conejo J, Dayo AF, Syed AZ, Mupparapu M. The digital clone: Intraoral scanning, face scans and cone beam computed tomography integration for diagnosis and treatment planning. Dent Clin North Am. 2021;65(3):529-53.
  • Strunga M, Urban R, Surovková J, Thurzo A. Artificial intelligence systems assisting in the assessment of the course and retention of orthodontic treatment. Healthcare (Basel). 2023;11(5):683.
  • Abesi F, Maleki M, Zamani M. Diagnostic performance of artificial intelligence using cone-beam computed tomography imaging of the oral and maxillofacial region: A scoping review and meta-analysis. Imaging Sci Dent. 2023;53(2):101-8.
  • Bianchi J, Mendonca G, Gillot M, Oh H, Park J, Turkestani NA, et al. Three-dimensional digital applications for implant space planning in orthodontics: A narrative review. J World Fed Orthod. 2022;11(6):207-15.
  • Schwendicke F, Chaurasia A, Arsiwala L, Lee JH, Elhennawy K, Jost-Brinkmann PG, et al. Deep learning for cephalometric landmark detection: Systematic review and meta-analysis. Clin Oral Investig. 2021;25(7):4299-309.
  • Chung EJ, Yang BE, Park IY, Yi S, On SW, Kim YH, et al. Effectiveness of cone-beam computed tomography-generated cephalograms using artificial intelligence cephalometric analysis. Sci Rep. 2022;12(1):20585.
  • Khanagar SB, Al-Ehaideb A, Vishwanathaiah S, Maganur PC, Patil S, Naik S, et al. Scope and performance of artificial intelligence technology in orthodontic diagnosis, treatment planning, and clinical decision-making: A systematic review. J Dent Sci. 2021;16(1):482-92.
  • Kravitz ND, Kusnoto B, BeGole E, Obrez A, Agran B. How well does Invisalign work? A prospective clinical study evaluating the efficacy of tooth movement with Invisalign. Am J Orthod Dentofacial Orthop. 2009;135(1):27-35.
  • Auconi P, Gili T, Capuani S, Saccucci M, Caldarelli G, Polimeni A, Di Carlo G. The validity of machine learning procedures in orthodontics: What is still missing? J Pers Med. 2022;12(6):957.
  • Thurzo A, Kurilová V, Varga I. Artificial intelligence in orthodontic smart application for treatment coaching and its ımpact on clinical performance of patients monitored with AI-Telehealth system. Healthcare (Basel). 2021;9(12):1695.
  • van Riet TCT, Chin Jen Sem KTH, Ho JTF, Spijker R, Kober J, de Lange J. Robot technology in dentistry, part two of a systematic review: An overview of initiatives. Dent Mater. 2021;37(8):1227-36.
  • Adel S, Zaher A, El Harouni N, Venugopal A, Premjani P, Vaid N. Robotic applications in orthodontics: Changing the face of contemporary clinical care. Biomed Res Int. 2021;2021:9954615.
  • Gianfrancesco MA, Tamang S, Yazdany J, Schmajuk G. Potential biases in machine learning algorithms using electronic health record data. JAMA Intern Med. 2018;178(11):1544-7.
  • Gerke S, Minssen T, Cohen G. Ethical and legal challenges of artificial intelligence-driven healthcare. In: Artificial Intelligence in Healthcare, 2020;295-336.
  • Lopes IM, Guarda T, Oliveira P. General data protection regulation in health clinics. J Med Syst. 2020;44(2):53.
  • Schwendicke F, Samek W, Krois J. Artificial intelligence in dentistry: Chances and challenges. J Dent Res. 2020;99(7):769-74.
  • Fatima A, Shafi I, Afzal H, Díez IT, Lourdes DRM, Breñosa J, et al. Advancements in dentistry with artificial intelligence: Current clinical applications and future perspectives. Healthcare (Basel). 2022;10(11):2188.

YAPAY ZEKANIN ORTODONTİK TEDAVİDEKİ ROLÜ

Year 2023, Volume: 25 Issue: 2, 340 - 346, 31.08.2023
https://doi.org/10.24938/kutfd.1335382

Abstract

Yapay zeka, genellikle 21. yüzyılın en dönüştürücü teknolojisi olarak kabul edilmektedir. Yapay zekanın giderek daha fazla entegre edildiği alanlardan biri de sağlık hizmetleridir. Bu geniş kapsam içinde, yapay zekanın derin etkilerini görmeye başlayan özel bir disiplin ise ortodonti alanıdır. Bu derlemenin amacı, yapay zekanın ortodontide entegrasyonu üzerine daha fazla tartışmayı teşvik etmek ve hastanın bakımında artan doğruluk, verimlilik ve kişiselleştirme getirerek bu alanı dönüştürme ve geliştirme potansiyeline odaklanmaktır.

Supporting Institution

yok

Project Number

yok

Thanks

yok

References

  • Ishii E, Ebner DK, Kimura S, Agha-Mir-Salim L, Uchimido R, Celi LA. The advent of medical artificial intelligence: lessons from the Japanese approach. J Intensive Care. 2020;8:35.
  • Chen H, Chen S, Zhao J. Integrated design of financial self-service terminal based on artificial intelligence voice ınteraction. Front Psychol. 2022;13:850092.
  • Theodosiou AA, Read RC. Artificial intelligence, machine learning and deep learning: Potential resources for the infection clinician. J Infect. 2023:S0163-4453(23)00379-1.
  • Jiang F, Jiang Y, Zhi H, Dong Y, Li H, Ma S, et al. Artificial intelligence in healthcare: Past, present and future. Stroke Vasc Neurol. 2017;2(4):230-43.
  • Liu J, Chen Y, Li S, Zhao Z, Wu Z. Machine learning in orthodontics: Challenges and perspectives. Adv Clin Exp Med. 2021;30(10):1065-74.
  • Israni ST, Verghese A.  Humanizing artificial intelligence. JAMA. 2019;321(1):29-30.
  • Ghafari JG. Centennial inventory: the changing face of orthodontics. Am J Orthod Dentofacial Orthop. 2015;148(5):732-9.
  • Conejo J, Dayo AF, Syed AZ, Mupparapu M. The digital clone: Intraoral scanning, face scans and cone beam computed tomography integration for diagnosis and treatment planning. Dent Clin North Am. 2021;65(3):529-53.
  • Strunga M, Urban R, Surovková J, Thurzo A. Artificial intelligence systems assisting in the assessment of the course and retention of orthodontic treatment. Healthcare (Basel). 2023;11(5):683.
  • Abesi F, Maleki M, Zamani M. Diagnostic performance of artificial intelligence using cone-beam computed tomography imaging of the oral and maxillofacial region: A scoping review and meta-analysis. Imaging Sci Dent. 2023;53(2):101-8.
  • Bianchi J, Mendonca G, Gillot M, Oh H, Park J, Turkestani NA, et al. Three-dimensional digital applications for implant space planning in orthodontics: A narrative review. J World Fed Orthod. 2022;11(6):207-15.
  • Schwendicke F, Chaurasia A, Arsiwala L, Lee JH, Elhennawy K, Jost-Brinkmann PG, et al. Deep learning for cephalometric landmark detection: Systematic review and meta-analysis. Clin Oral Investig. 2021;25(7):4299-309.
  • Chung EJ, Yang BE, Park IY, Yi S, On SW, Kim YH, et al. Effectiveness of cone-beam computed tomography-generated cephalograms using artificial intelligence cephalometric analysis. Sci Rep. 2022;12(1):20585.
  • Khanagar SB, Al-Ehaideb A, Vishwanathaiah S, Maganur PC, Patil S, Naik S, et al. Scope and performance of artificial intelligence technology in orthodontic diagnosis, treatment planning, and clinical decision-making: A systematic review. J Dent Sci. 2021;16(1):482-92.
  • Kravitz ND, Kusnoto B, BeGole E, Obrez A, Agran B. How well does Invisalign work? A prospective clinical study evaluating the efficacy of tooth movement with Invisalign. Am J Orthod Dentofacial Orthop. 2009;135(1):27-35.
  • Auconi P, Gili T, Capuani S, Saccucci M, Caldarelli G, Polimeni A, Di Carlo G. The validity of machine learning procedures in orthodontics: What is still missing? J Pers Med. 2022;12(6):957.
  • Thurzo A, Kurilová V, Varga I. Artificial intelligence in orthodontic smart application for treatment coaching and its ımpact on clinical performance of patients monitored with AI-Telehealth system. Healthcare (Basel). 2021;9(12):1695.
  • van Riet TCT, Chin Jen Sem KTH, Ho JTF, Spijker R, Kober J, de Lange J. Robot technology in dentistry, part two of a systematic review: An overview of initiatives. Dent Mater. 2021;37(8):1227-36.
  • Adel S, Zaher A, El Harouni N, Venugopal A, Premjani P, Vaid N. Robotic applications in orthodontics: Changing the face of contemporary clinical care. Biomed Res Int. 2021;2021:9954615.
  • Gianfrancesco MA, Tamang S, Yazdany J, Schmajuk G. Potential biases in machine learning algorithms using electronic health record data. JAMA Intern Med. 2018;178(11):1544-7.
  • Gerke S, Minssen T, Cohen G. Ethical and legal challenges of artificial intelligence-driven healthcare. In: Artificial Intelligence in Healthcare, 2020;295-336.
  • Lopes IM, Guarda T, Oliveira P. General data protection regulation in health clinics. J Med Syst. 2020;44(2):53.
  • Schwendicke F, Samek W, Krois J. Artificial intelligence in dentistry: Chances and challenges. J Dent Res. 2020;99(7):769-74.
  • Fatima A, Shafi I, Afzal H, Díez IT, Lourdes DRM, Breñosa J, et al. Advancements in dentistry with artificial intelligence: Current clinical applications and future perspectives. Healthcare (Basel). 2022;10(11):2188.
There are 24 citations in total.

Details

Primary Language Turkish
Subjects Health Services and Systems (Other)
Journal Section Review
Authors

Alaattin Tekeli 0009-0002-0366-1659

Project Number yok
Publication Date August 31, 2023
Submission Date July 31, 2023
Published in Issue Year 2023 Volume: 25 Issue: 2

Cite

APA Tekeli, A. (2023). YAPAY ZEKANIN ORTODONTİK TEDAVİDEKİ ROLÜ. Kırıkkale Üniversitesi Tıp Fakültesi Dergisi, 25(2), 340-346. https://doi.org/10.24938/kutfd.1335382
AMA Tekeli A. YAPAY ZEKANIN ORTODONTİK TEDAVİDEKİ ROLÜ. Kırıkkale Uni Med J. August 2023;25(2):340-346. doi:10.24938/kutfd.1335382
Chicago Tekeli, Alaattin. “YAPAY ZEKANIN ORTODONTİK TEDAVİDEKİ ROLÜ”. Kırıkkale Üniversitesi Tıp Fakültesi Dergisi 25, no. 2 (August 2023): 340-46. https://doi.org/10.24938/kutfd.1335382.
EndNote Tekeli A (August 1, 2023) YAPAY ZEKANIN ORTODONTİK TEDAVİDEKİ ROLÜ. Kırıkkale Üniversitesi Tıp Fakültesi Dergisi 25 2 340–346.
IEEE A. Tekeli, “YAPAY ZEKANIN ORTODONTİK TEDAVİDEKİ ROLÜ”, Kırıkkale Uni Med J, vol. 25, no. 2, pp. 340–346, 2023, doi: 10.24938/kutfd.1335382.
ISNAD Tekeli, Alaattin. “YAPAY ZEKANIN ORTODONTİK TEDAVİDEKİ ROLÜ”. Kırıkkale Üniversitesi Tıp Fakültesi Dergisi 25/2 (August 2023), 340-346. https://doi.org/10.24938/kutfd.1335382.
JAMA Tekeli A. YAPAY ZEKANIN ORTODONTİK TEDAVİDEKİ ROLÜ. Kırıkkale Uni Med J. 2023;25:340–346.
MLA Tekeli, Alaattin. “YAPAY ZEKANIN ORTODONTİK TEDAVİDEKİ ROLÜ”. Kırıkkale Üniversitesi Tıp Fakültesi Dergisi, vol. 25, no. 2, 2023, pp. 340-6, doi:10.24938/kutfd.1335382.
Vancouver Tekeli A. YAPAY ZEKANIN ORTODONTİK TEDAVİDEKİ ROLÜ. Kırıkkale Uni Med J. 2023;25(2):340-6.

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