ARTIFICIAL INTELLIGENCE IN DENTISTRY
Keywords:
electronic brain, deep learning artificial intelligence, convolutional neural networks (cnn), ai, cnn, ann, artificial neural network, applications of ai, artificial intelligence in dentistry, artificial intelligence.Abstract
AI is a powerful technology that can simulate human intelligence and perform complex tasks in various fields, including dentistry. One of the fields that can benefit from AI is endodontics, which deals with the diagnosis and treatment of the dental pulp and the surrounding tissues. AI models, such as convolutional neural networks and/or artificial neural networks, can be used for different purposes in endodontics, such as analyzing the root canal anatomy, predicting the survival of dental pulp stem cells, determining the working length, detecting root fractures and periapical lesions, and estimating the outcome of retreatment procedures. AI can also have potential applications in other aspects of endodontics, such as scheduling, patient management, drug interactions, prognostic diagnosis, and robotic endodontic surgery. AI has shown accuracy and precision in endodontics, especially in disease detection, assessment, and prediction. AI can help improve the quality and efficiency of endodontic diagnosis and treatment, which can lead to better endodontic outcomes. However, before implementing AI models in clinical practice, it is still necessary to further evaluate their cost-effectiveness, reliability, and feasibility.
References
Artificial Intelligence in Dentistry: Current Concepts and a Peep Into the Future. Alexander B, John S. Int J Adv Res. 2018;30:1105–1108. [Google Scholar]
Present and future of artificial intelligence in dentistry. Tandon D, Rajawat J. J Oral Biol Craniofac Res. 2020;10:391–396. [PMC free article] [PubMed] [Google Scholar]
Artificial intelligence in endodontics: Current applications and future directions. Aminoshariae A, Kulild J, Nagendrababu V. J Endod. 2021;47:1352–1357. [PubMed] [Google Scholar]
Artificial intelligence in dentistry. Deshmukh S. J Int Clin Dent Res Organ. 2018;10:47. [Google Scholar]
Application and performance of artificial intelligence technology in oral cancer diagnosis and prediction of prognosis: A systematic review. Khanagar SB, Naik S, Al Kheraif AA, et al. Diagnostics (Basel) 2021;11 [PMC free article] [PubMed] [Google Scholar]
Effectiveness of artificial intelligence applications designed for endodontic diagnosis, decision-making, and prediction of prognosis: A systematic review. Boreak N. J Contemp Dent Pract. 2020;30:926–934. [PubMed] [Google Scholar]
Use of artificial intelligence in dentistry: Current clinical trends and research advances. Nguyen TT, Larrivée N, Lee A, Bilaniuk O, Durand R. https://pubmed.ncbi.nlm.nih.gov/34343070/ J Can Dent Assoc. 2021;87:0. [PubMed] [Google Scholar]
Artificial intelligence in dentistry. Meghil MM, Rajpurohit P, Awad ME, McKee J, Shahoumi LA, Ghaly M. Dent Rev. 2022;2:100009. [Google Scholar]
Artificial Intelligence in dentistry: Concepts, applications and research challenges. Babu A, Andrew Onesimu J, Martin Sagayam K. 3:1074. [Google Scholar]
Brodie ML. Springer International Publishing; 2019. What Is Data Science? [Google Scholar]
Big data and big data analytics: Concepts, types and technologies. Riahi Y, Riahi S. Int J Res Eng. 2018;5:524–528. [Google Scholar]
Artificial Intelligence in dentistry: Chances and challenges. Schwendicke F, Samek W, Krois J. J Dent Res. 2020;99:769–774. [PMC free article] [PubMed] [Google Scholar]
Application of artificial intelligence in dentistry. Shan T, Tay FR, Gu L. J Dent Res. 2021;100:232–244. [PubMed] [Google Scholar]
Artificial intelligence in dentistry-narrative review. Ossowska A, Kusiak A, Świetlik D. Int J Environ Res Public Health. 2022;19 [PMC free article] [PubMed] [Google Scholar]
The role of neural artificial intelligence for diagnosis and treatment planning in endodontics: A qualitative review. Asiri AF, Altuwalah AS. Saudi Dent J. 2022;34:270–281. [PMC free article] [PubMed] [Google Scholar]
Towards artificial intelligence for clinical stroke care. Leslie-Mazwi TM, Lev MH. Nat Rev Neurol. 2020;16:5–6. [PubMed] [Google Scholar]
Radiolucent inflammatory jaw lesions: a twenty-year analysis. Becconsall-Ryan K, Tong D, Love RM. Int Endod J. 2010;43:859–865. [PubMed] [Google Scholar]
Periapical lucency around the tooth: radiologic evaluation and differential diagnosis. Chapman MN, Nadgir RN, Akman AS, Saito N, Sekiya K, Kaneda T, Sakai O. Radiographics. 2013;33:0–32. [PubMed] [Google Scholar]
New dimensions in endodontic imaging: part 1. Conventional and alternative radiographic systems. Patel S, Dawood A, Whaites E, Pitt Ford T. Int Endod J. 2009;42:447–462. [PubMed] [Google Scholar]
Diagnostic accuracy of cone-beam computed tomography and conventional radiography on apical periodontitis: A systematic review and meta-analysis. Leonardi Dutra K, Haas L, Porporatti AL, et al. J Endod. 2016;42:356–364. [PubMed] [Google Scholar]
The use and performance of artificial intelligence applications in dental and maxillofacial radiology: A systematic review. Hung K, Montalvao C, Tanaka R, Kawai T, Bornstein MM. Dentomaxillofac Radiol. 2020;49:20190107. [PMC free article] [PubMed] [Google Scholar]