Okklyuziya tahlilida sun’iy intellekt texnologiyalarini qo‘llash va stomatologik menejment tizimi samaradorligini optimallashtirish
Safarov M.T
Odilova M.U
Xabilov D.N
Qosimova K.A
Olimjonova N.O
Dadabayeva M.U
Azimov R.I
Keywords: sun’iy intellekt, okklyuziya tahlili, raqamli stomatologiya, mashinaviy o‘qitish, stomatologik menejment, klinik qaror qabul qilish, okklyuzion kuch taqsimoti
Abstract
Ushbu sharhning maqsadi okklyuziya tahlilida sun’iy intellekt (SI)ni qo‘llash imkoniyatlarini baholash hamda uning stomatologik menejment samaradorligiga ta’sirini aniqlashdan iborat. Tahlil so‘nggi klinik tadqiqotlar, raqamli stomatologiya hisobotlari va ekspertlar konsensus hujjatlari asosida amalga oshirildi. Natijalar shuni ko‘rsatadiki, mashinaviy o‘qitish algoritmlari va raqamli okklyuzion tahlil vositalarini o‘z ichiga olgan SI tizimlari okklyuzion kontaktlarni aniqlash, kuch taqsimotini baholash hamda davolash rejasini tuzishda aniqlikni sezilarli darajada oshiradi.
References
1. Schwendicke, F., Samek, W., & Krois, J. (2020). Artificial intelligence in dentistry: Chances and challenges. Journal of Dental Research, 99(7), 769–774. https://doi.org/10.1177/0022034520915714
2. Schwendicke, F., Golla, T., Dreher, M., & Krois, J. (2019). Convolutional neural networks for dental image diagnostics: A systematic review. Journal of Dentistry, 91, 103226. https://doi.org/10.1016/j.jdent.2019.103226
3. Krois, J., Ekert, T., Meinhold, L., et al. (2019). Deep learning for the radiographic detection of periodontal bone loss. Scientific Reports, 9, 8495. https://doi.org/10.1038/s41598-019-44839-3
4. Revilla-León, M., & Özcan, M. (2019). Additive manufacturing technologies used for processing polymers in dentistry. Journal of Prosthodontics, 28(2), 146–158. https://doi.org/10.1111/jopr.12801
5. Mangano, F., Gandolfi, A., Luongo, G., & Logozzo, S. (2017). Intraoral scanners in dentistry: A review of the current literature. BMC Oral Health, 17, 149. https://doi.org/10.1186/s12903-017-0442-x
6. Joda, T., Ferrari, M., Gallucci, G. O., Wittneben, J. G., & Brägger, U. (2017). Digital technology in fixed implant prosthodontics. Periodontology 2000, 73(1), 178–192.
7. Miyazaki, T., Hotta, Y., Kunii, J., Kuriyama, S., & Tamaki, Y. (2009). A review of dental CAD/CAM: Current status and future perspectives. Journal of Prosthodontic Research, 53(1), 1–7.
8. Kerstein, R. B. (2015). Combining technologies: A computerized occlusal analysis system synchronized with a computerized electromyography system. Cranio, 33(3), 189–198.
9. Sierpinska, T., & Golebiewska, M. (2020). Digital occlusal analysis in prosthetic dentistry. Advances in Clinical and Experimental Medicine, 29(2), 255–260.
10. Dawood, A., Marti Marti, B., Sauret-Jackson, V., & Darwood, A. (2015). 3D printing in dentistry. British Dental Journal, 219(11), 521–529.
11. Javaid, M., & Haleem, A. (2020). Artificial intelligence applications in dentistry. Dental Journal, 8(2), 44.
12. Khanagar, S. B., Al-Ehaideb, A., Maganur, P. C., et al. (2021). Developments, application, and performance of artificial intelligence in dentistry – A systematic review. Journal of Dental Sciences, 16(1), 508–522.
13. Hung, K., Montalvao, C., Tanaka, R., et al. (2020). The use and performance of artificial intelligence applications in dentistry: A systematic review. Journal of Dentistry, 103, 103434.
14. Lee, J. H., Kim, D. H., Jeong, S. N., & Choi, S. H. (2018). Detection and diagnosis of dental caries using a deep learning-based convolutional neural network. Journal of Dentistry, 77, 106–111.
15. Patzelt, S. B. M., Emmanouilidi, A., Stampf, S., Strub, J. R., & Att, W. (2014). Accuracy of full-arch scans using intraoral scanners. Clinical Oral Investigations, 18, 1687–1694.
16. Rekow, D. (2017). Digital dentistry: The new state of the art—Is it disruptive or destructive? Dental Materials, 33(7), 739–741.
17. Mörmann, W. H. (2006). The evolution of the CEREC system. Journal of the American Dental Association, 137(Suppl), 7S–13S.
