Applications of AI in Endodontics and Restorative Dentistry
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-43827-1_5
Reference24 articles.
1. American Association of Endodontists. Endodontic Case Difficulty Assessment Form and Guidelines. https://www.aae.org
2. Bayrakdar IS, Orhan K, Çelik Ö, et al. A U-Net approach to apical lesion segmentation on panoramic radiographs. Biomed Res Int. 2022;2022:7035367. Published 2022 Jan 15. https://doi.org/10.1155/2022/7035367.
3. Calazans MAA, Ferreira FABS, Alcoforado MLMG, Santos AD, Pontual ADA, Madeiro F. Automatic classification system for periapical lesions in cone-beam computed tomography. Sensors (Basel). 2022;22(17):6481. Published 2022 Aug 28. https://doi.org/10.3390/s22176481.
4. Ekert T, Krois J, Meinhold L, et al. Deep learning for the radiographic detection of apical lesions. J Endod. 2019;45(7):917–922.e5. https://doi.org/10.1016/j.joen.2019.03.016.
5. Endres MG, Hillen F, Salloumis M, et al. Development of a deep learning algorithm for periapical disease detection in dental radiographs. Diagnostics (Basel). 2020;10(6):430. Published 2020 Jun 24. https://doi.org/10.3390/diagnostics10060430.
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