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Artificial Intelligence in Dentistry

Yıl 2025, Cilt: 5 Sayı: 1, 28 - 34, 27.06.2025

Cem Sahin , Enes Ekinci

Öz

Abstract
With the development of artificial intelligence that can imitate human way of thinking, many professions have developed innovative techniques and technologies in their fields. One of these is the profession of dentistry. This profession is already a field where human-machine interaction is mandatory. However, artificial intelligence has taken this process a few steps higher. Artificial intelligence has made tremendous contributions in radiographic evaluations, prosthetic treatment planning, orthodontic treatment processes, surgery, in short, in all dental departments involving diagnosis and treatment.
This study aimed to evaluate the development process of artificial intelligence and the contributions of this development to dentistry in detail through dental departments.

Keywords: Artificial Intelligence, dental automation, dental cad-cam systems

Anahtar Kelimeler

Artificial Intelligence dental automation dental cad-cam systems

Etik Beyan

This study does not require ethics committee approval.

Kaynakça

  • R. Cordeschi, “AI turns fifty: Revisiting its origins,” Applied Artificial Intelligence, vol. 21, no.4, Apr., pp. 259-279, 2007.
  • C. Bassett, “The computational therapeutic: exploring Weizenbaum’s ELIZA as a history of the present,” AI&Soc, vol. 34, no. 4, Feb., pp. 803-812, 2018.
  • F. Narcross, “Artificial nervous systems—A new paradigm for artificial intelligence,” Patterns, vol. 2, no. 6, June, pp. 1-3, 2021.
  • E. Okewu, P. Adewole, S. Misra, R. Maskeliunas, and R. Damasevicius, “Artificial Neural Networks for Educational Data Mining in Higher Education: A Systematic Literature Review,” Applied Artificial Intelligence, vol. 35, no. 13, Oct., pp. 983–1002, 2021.
  • A. Ossowska, A. Kusiak, and D. Świetlik, “Artificial Intelligence in Dentistry—Narrative Review,” International Journal of Environmental Research and Public Health, vol. 19, no. 6 , Mar., pp. 1-10, 2022.
  • A. Kane and A. Hussain, “Artificial Neural Networks - An overview,” Indian Drugs, vol.30, no. 5, Jan., pp.168-168, 1993.
  • W. Salah Alaloul and A. Hannan Qureshi, “Data Processing Using Artificial Neural Networks,” Dynamic Data Assimilation - Beating the Uncertainties, CA: IntechOpen 2020.
  • N. Ahmed, M. Ş. Abbasi, F. Züberi, W. Qamar, M. S. B. Halim, A. Maksud and M. H. Alam, “Artificial Intelligence Techniques: Analysis, Application, and Outcome in Dentistry - A Systematic Review,” BioMed Research International, vol. 2021, no. 22, June, pp. 1-15, 2021.
  • X. Liu, L. Song, S. Liu, and Y. Zhang, “A review of deep-learning-based medical image segmentation methods,” Sustainability (Switzerland), vol. 13, no. 3, Jan., pp. 1-19, 2021.
  • O. Miloglu, M. T. Guller, and Z. T. Tosun, “The Use of Artificial Intelligence in Dentistry Practices,” The Eurasian Journal of Medicine, vol. 54, no. 1, Dec., pp. 34-42, 2022.
  • M. T. Alharbi and M. M. Almutiq, “Prediction of Dental Implants Using Machine Learning Algorithms,” Journal of Healthcare Engineering, vol. 20, no. 1, Jan., pp. 1-12, 2022.
  • Planet DDS, planetdds.com/apteryx/ai/, para. 1, [Online]. Available: https://www.planetdds.com/cloud9/. [Accessed: Jan. 18, 2025].
  • W. Stawska, M. Milek, K. Kwaśniak, A. Foryś, M. Banach, A. Niemczyk, M. Ślusarczyk, A. Magierska, Z. Kotowicz and W. Kmiotek, “The use of artificial intelligence in radiology: new possibilities for diagnostic imaging. A literature review,” Quality in Sport, vol. 16, no. 1, Jul., pp. 1-14, 2024.
  • R. H. Putra, C. Doi, N. Yoda, E. R. Astuti, and K. Sasaki, “Current applications and development of artificial intelligence for digital dental radiography,” Dentomaxillofac Radiology, vol. 51, no. 1, Jan., pp. 1-12, 2022.
  • A. Tariq, F. B. Nakhi, F. Salah, G. Eltayeb, G. J. Abdulla, N. Necim, S. A. Khedr, S. Elkerdasy, N. Al-Rawi, S. Alkawas, M. Muhammed and Ş. R. Shetty, “Efficiency and accuracy of artificial intelligence in the radiographic detection of periodontal bone loss: A systematic review,” Imaging Science in Dentistry, vol. 53 no. 3, Sep., pp. 193-198, 2023.
  • D. Ismail and Edi Gunawan, “Study of the Use of AI (Artificial Intelligence) in the Field of Radiology and Imaging,” Sriwijaya Journal of Radiology and Imaging Research, vol. 1, no. 2, Nov., pp. 34-38, 2023.
  • J. Kühnisch, O. Meyer, M. Hesenius, R. Hickel, and V. Gruhn, “Caries Detection on Intraoral Images Using Artificial Intelligence,” Journal of Dental Research, vol. 101, no. 2, Feb., pp. 158-165, 2022.
  • SmileCloud Biometrics,” smilecloud.com, para. 1, [Online]. Available: https://smilecloud.com/#intuitive. [Accessed: Jan. 20, 2025].
  • “Digital dentistry: definition, advantages and development,” 3shape.com, para 1, Nov. 14, 2024. [Online]. Available: https://www.3shape.com/en/blog/digital-dentistry/intro-digital-dentistry. [Accessed: Jan. 20, 2025].
  • “Create fully digital 3d mock-ups: Quick and easy,” rebel.dental.com, [Online]. Available: https://rebel.dental. [Accessed: Jan. 19, 2025].
  • S. A. Yousief, D. K. Gamlo, M. A. Dewan, S. K. Barahim, R. O. Alashbat and I. H. Alhifny, “Significance of Facebow Transfer,” EC Dental Science, vol. 19, no. 2, Jan., pp. 01-05, 2020.
  • W. Sutradhar, SunilK. Mishra, and R. Chowdhary, “Uses, accuracy and limitations of semiadjustable articulators in dentistry: a systematic review,” Tanta Dental Journal, vol. 16, no. 3, April, pp. 121-135, 2019.
  • J. C. Kois, D. E. Kois, J. M. Zeitler, and J. Martin, “Digital to Analog Facially Generated Interchangeable Facebow Transfer: Capturing a Standardized Reference Position,” Journal of Prosthodontics, vol. 31, no. 1, Mar., pp. 13–22, 2022.
  • S. B. Khanagar, A. El-Ehaideb, S. Vişvanathaiah, P. C. Maganu, Ş. Patil, S. Naik, H. A. Baeshen and S. S. Sarode, “Scope and performance of artificial intelligence technology in orthodontic diagnosis, treatment planning, and clinical decision-making - A systematic review,” Journal of Dental Sciences, vol. 16, no. 1, Jan., pp. 482-492, 2021
  • F. Albalawi and K. A. Alamoud, “Trends and Application of Artificial Intelligence Technology in Orthodontic Diagnosis and Treatment Planning—A Review,” Applied Sciences, vol. 12, no. 22, Nov., pp. 1-20, 2022.
  • W. Alswajy, H. Baeshen, G. Al-Turki, and F. Alsulaimani, “The Reliability of ClinCheck® Accuracy before and after Invisalign® Treatment—A Multicenter Retrospective Study,” Applied Sciences (Switzerland), vol. 13, no. 8, Apr., pp. 1-8, 2023.
  • DentalMonitoring – AI-powered remote monitoring for orthodontics, dentalmonitoring.com, [Online]. Available: https://dentalmonitoring.com/dental-monitoring/. [Accessed: Jan. 20, 2025].
  • P. A. Lyakhov, A. A. Dolgalev, U. A. Lyakhova, A. A. Muraev, K. E. Zolotayev, and D. Y. Semerikov, “Neural network system for analyzing statistical factors of patients for predicting the survival of dental implants,” Front Neuroinform, vol. 16, no. 1, Dec., pp. 1-15, 2022.
  • Digital solutions, nobelbiocare.com, [Online]. Available: https://www.nobelbiocare.com/en-int/digital-dentistry-solutions. [Accessed Jan. 19, 2025].

Diş Hekimliğinde Yapay Zeka

Yıl 2025, Cilt: 5 Sayı: 1, 28 - 34, 27.06.2025

Cem Sahin , Enes Ekinci

Öz

özet
İnsan düşünce tarzını taklit edebilen yapay zekanın gelişmesiyle birlikte birçok meslek kendi alanlarında yenilikçi teknikler ve teknolojiler geliştirmiştir. Bunlardan biri de diş hekimliği mesleğidir. Bu meslek zaten insan-makine etkileşiminin zorunlu olduğu bir alandır. Ancak yapay zeka bu süreci birkaç adım öteye taşımıştır. Yapay zeka radyografik değerlendirmelerde, protez tedavi planlamasında, ortodontik tedavi süreçlerinde, cerrahide, kısacası teşhis ve tedaviyi içeren tüm diş hekimliği bölümlerinde muazzam katkılarda bulunmuştur.
Bu çalışma yapay zekanın gelişim sürecini ve bu gelişimin diş hekimliğine katkılarını diş hekimliği bölümleri üzerinden detaylı olarak değerlendirmeyi amaçlamıştır.

Anahtar kelimeler: Yapay zeka, diş hekimliği otomasyonu, diş hekimliği cad-cam sistemleri

Anahtar Kelimeler

yapay zeka dental otomasyon dental cad-cam sistemler

Kaynakça

  • R. Cordeschi, “AI turns fifty: Revisiting its origins,” Applied Artificial Intelligence, vol. 21, no.4, Apr., pp. 259-279, 2007.
  • C. Bassett, “The computational therapeutic: exploring Weizenbaum’s ELIZA as a history of the present,” AI&Soc, vol. 34, no. 4, Feb., pp. 803-812, 2018.
  • F. Narcross, “Artificial nervous systems—A new paradigm for artificial intelligence,” Patterns, vol. 2, no. 6, June, pp. 1-3, 2021.
  • E. Okewu, P. Adewole, S. Misra, R. Maskeliunas, and R. Damasevicius, “Artificial Neural Networks for Educational Data Mining in Higher Education: A Systematic Literature Review,” Applied Artificial Intelligence, vol. 35, no. 13, Oct., pp. 983–1002, 2021.
  • A. Ossowska, A. Kusiak, and D. Świetlik, “Artificial Intelligence in Dentistry—Narrative Review,” International Journal of Environmental Research and Public Health, vol. 19, no. 6 , Mar., pp. 1-10, 2022.
  • A. Kane and A. Hussain, “Artificial Neural Networks - An overview,” Indian Drugs, vol.30, no. 5, Jan., pp.168-168, 1993.
  • W. Salah Alaloul and A. Hannan Qureshi, “Data Processing Using Artificial Neural Networks,” Dynamic Data Assimilation - Beating the Uncertainties, CA: IntechOpen 2020.
  • N. Ahmed, M. Ş. Abbasi, F. Züberi, W. Qamar, M. S. B. Halim, A. Maksud and M. H. Alam, “Artificial Intelligence Techniques: Analysis, Application, and Outcome in Dentistry - A Systematic Review,” BioMed Research International, vol. 2021, no. 22, June, pp. 1-15, 2021.
  • X. Liu, L. Song, S. Liu, and Y. Zhang, “A review of deep-learning-based medical image segmentation methods,” Sustainability (Switzerland), vol. 13, no. 3, Jan., pp. 1-19, 2021.
  • O. Miloglu, M. T. Guller, and Z. T. Tosun, “The Use of Artificial Intelligence in Dentistry Practices,” The Eurasian Journal of Medicine, vol. 54, no. 1, Dec., pp. 34-42, 2022.
  • M. T. Alharbi and M. M. Almutiq, “Prediction of Dental Implants Using Machine Learning Algorithms,” Journal of Healthcare Engineering, vol. 20, no. 1, Jan., pp. 1-12, 2022.
  • Planet DDS, planetdds.com/apteryx/ai/, para. 1, [Online]. Available: https://www.planetdds.com/cloud9/. [Accessed: Jan. 18, 2025].
  • W. Stawska, M. Milek, K. Kwaśniak, A. Foryś, M. Banach, A. Niemczyk, M. Ślusarczyk, A. Magierska, Z. Kotowicz and W. Kmiotek, “The use of artificial intelligence in radiology: new possibilities for diagnostic imaging. A literature review,” Quality in Sport, vol. 16, no. 1, Jul., pp. 1-14, 2024.
  • R. H. Putra, C. Doi, N. Yoda, E. R. Astuti, and K. Sasaki, “Current applications and development of artificial intelligence for digital dental radiography,” Dentomaxillofac Radiology, vol. 51, no. 1, Jan., pp. 1-12, 2022.
  • A. Tariq, F. B. Nakhi, F. Salah, G. Eltayeb, G. J. Abdulla, N. Necim, S. A. Khedr, S. Elkerdasy, N. Al-Rawi, S. Alkawas, M. Muhammed and Ş. R. Shetty, “Efficiency and accuracy of artificial intelligence in the radiographic detection of periodontal bone loss: A systematic review,” Imaging Science in Dentistry, vol. 53 no. 3, Sep., pp. 193-198, 2023.
  • D. Ismail and Edi Gunawan, “Study of the Use of AI (Artificial Intelligence) in the Field of Radiology and Imaging,” Sriwijaya Journal of Radiology and Imaging Research, vol. 1, no. 2, Nov., pp. 34-38, 2023.
  • J. Kühnisch, O. Meyer, M. Hesenius, R. Hickel, and V. Gruhn, “Caries Detection on Intraoral Images Using Artificial Intelligence,” Journal of Dental Research, vol. 101, no. 2, Feb., pp. 158-165, 2022.
  • SmileCloud Biometrics,” smilecloud.com, para. 1, [Online]. Available: https://smilecloud.com/#intuitive. [Accessed: Jan. 20, 2025].
  • “Digital dentistry: definition, advantages and development,” 3shape.com, para 1, Nov. 14, 2024. [Online]. Available: https://www.3shape.com/en/blog/digital-dentistry/intro-digital-dentistry. [Accessed: Jan. 20, 2025].
  • “Create fully digital 3d mock-ups: Quick and easy,” rebel.dental.com, [Online]. Available: https://rebel.dental. [Accessed: Jan. 19, 2025].
  • S. A. Yousief, D. K. Gamlo, M. A. Dewan, S. K. Barahim, R. O. Alashbat and I. H. Alhifny, “Significance of Facebow Transfer,” EC Dental Science, vol. 19, no. 2, Jan., pp. 01-05, 2020.
  • W. Sutradhar, SunilK. Mishra, and R. Chowdhary, “Uses, accuracy and limitations of semiadjustable articulators in dentistry: a systematic review,” Tanta Dental Journal, vol. 16, no. 3, April, pp. 121-135, 2019.
  • J. C. Kois, D. E. Kois, J. M. Zeitler, and J. Martin, “Digital to Analog Facially Generated Interchangeable Facebow Transfer: Capturing a Standardized Reference Position,” Journal of Prosthodontics, vol. 31, no. 1, Mar., pp. 13–22, 2022.
  • S. B. Khanagar, A. El-Ehaideb, S. Vişvanathaiah, P. C. Maganu, Ş. Patil, S. Naik, H. A. Baeshen and S. S. Sarode, “Scope and performance of artificial intelligence technology in orthodontic diagnosis, treatment planning, and clinical decision-making - A systematic review,” Journal of Dental Sciences, vol. 16, no. 1, Jan., pp. 482-492, 2021
  • F. Albalawi and K. A. Alamoud, “Trends and Application of Artificial Intelligence Technology in Orthodontic Diagnosis and Treatment Planning—A Review,” Applied Sciences, vol. 12, no. 22, Nov., pp. 1-20, 2022.
  • W. Alswajy, H. Baeshen, G. Al-Turki, and F. Alsulaimani, “The Reliability of ClinCheck® Accuracy before and after Invisalign® Treatment—A Multicenter Retrospective Study,” Applied Sciences (Switzerland), vol. 13, no. 8, Apr., pp. 1-8, 2023.
  • DentalMonitoring – AI-powered remote monitoring for orthodontics, dentalmonitoring.com, [Online]. Available: https://dentalmonitoring.com/dental-monitoring/. [Accessed: Jan. 20, 2025].
  • P. A. Lyakhov, A. A. Dolgalev, U. A. Lyakhova, A. A. Muraev, K. E. Zolotayev, and D. Y. Semerikov, “Neural network system for analyzing statistical factors of patients for predicting the survival of dental implants,” Front Neuroinform, vol. 16, no. 1, Dec., pp. 1-15, 2022.
  • Digital solutions, nobelbiocare.com, [Online]. Available: https://www.nobelbiocare.com/en-int/digital-dentistry-solutions. [Accessed Jan. 19, 2025].
Toplam 29 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Yapay Zeka (Diğer)
Bölüm Reviews
Yazarlar

Cem Sahin 0000-0002-1301-8328

Enes Ekinci 0009-0002-0559-3477

Yayımlanma Tarihi 27 Haziran 2025
Gönderilme Tarihi 27 Ocak 2025
Kabul Tarihi 23 Haziran 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 5 Sayı: 1

Kaynak Göster

IEEE C. Sahin ve E. Ekinci, “Artificial Intelligence in Dentistry”, Journal of Artificial Intelligence and Data Science, c. 5, sy. 1, ss. 28–34, 2025.
 Kapak Resmi İndir

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