The Limitless Potential of Artificial Intelligence in Paediatric Dentistry AI in Paediatric Dentistry
Main Article Content
Abstract
Background: The integration of artificial intelligence (AI) in paedi-atric dentistry has grown signifi-cantly, offering new possibilities for diagnostics, treatment plan-ning, and patient care. AI’s capaci-ty to handle large datasets and generate accurate predictions is transforming dental practice.
Objective: This narrative review explores the potential applica-tions of AI in paediatric dentistry, focusing on its benefits, challeng-es, and future implications.
Methods: A comprehensive litera-ture review was conducted using databases such as PubMed, Sco-pus, and Web of Science. Relevant studies published between 2000 and 2023 were selected based on predefined inclusion criteria. The quality of the studies was ap-praised using the Joanna Briggs Institute tools.
Results: AI applications, including image analysis, diagnosis, treat-ment planning, and patient man-agement, show significant prom-ise in paediatric dentistry. AI-powered tools can improve diag-nostic accuracy, reduce treat-ment inconsistencies, and en-hance patient outcomes. Howev-er, challenges related to costs, complexity, and ethical concerns remain.
Conclusion: AI will not replace paediatric dentists but will serve as a valuable tool to support clini-cal decision-making. Future re-search should focus on overcom-ing current limitations and ensur-ing safe integration into clinical practice.
Article Details
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
DentalReach - Leading Dental Magazine - Dentistry Journal, News & Events. Artificial Neural Network in Pae-diatric Dentistry. February 21, 2022.
Baliga M. Artificial Intelligence: The Next Frontier in Pae-diatric Dentistry. J Indian Soc Pedod Prev Dent. 2019;37(4):315.
Brickley MR, Shepherd JP, Armstrong RA. Neural Net-works: A New Technique for Development of Decision Support Systems in Dentistry. J Dent. 1998;26(4):305-9.
Perlovsky LI. Neural Mechanisms of the Mind, Aristotle, Zadeh, and fMRI. IEEE Trans Neural Networks. 2010;21(5):718-33. doi:10.1109/TNN.2010.2041250.
Park WJ, Park JB. History and Application of Artificial Neural Networks in Dentistry. Eur J Dent. 2018;12(4):594-601. doi:10.4103/ejd.ejd_325_18.
Ferro AS, Nicholson K, Koka S. Innovative Trends in Im-plant Dentistry Training and Education: A Narrative Re-view. J Clin Med. 2019;8(10):1618.
Bindushree V, Sameen RJ, Vasudevan V, Shrihari TG, De-varaju D, Mathew NS. Artificial Intelligence: In Modern Dentistry. J Dent Res Rev. 2020;7:27.
Hassani H, Silva ES, Unger S, TajMazinani M, MacFeely S. Artificial Intelligence (AI) or Intelligence Augmentation (IA): What Is the Future? AI. 2020;1:143-55.
Carrillo-Perez F, Pecho OE, Morales JC, Paravina RD, Della Bona A, Ghinea R, Pulgar R, Pérez MD, Herrera LJ. Applications of Artificial Intelligence in Dentistry: A Comprehensive Review. J Esthet Restor Dent. 2021;29.
Sternberg RJ. Human Intelligence. Encyclopedia Britan-nica. https://www.britannica.com/science/human-intelligence-psychology. Accessed December 23, 2020.
Chen YW, Stanley K, Att W. Artificial Intelligence in Den-tistry: Current Applications and Future Perspectives. Quintessence Int. 2020;51:248-57.
Lee JH, Kim DH, Jeong SN, Choi SH. Detection and Di-agnosis of Dental Caries Using a Deep Learning-Based Convolutional Neural Network Algorithm. J Dent. 2018;77:106-11.
Hung M, Voss MW, Rosales MN, Li W, Su W, Xu J, Boun-sanga J, Ruiz-Negrón B, Licari FW. Application of Ma-chine Learning for Diagnostic Prediction of Root Caries. Gerodontology. 2019;36(4):395-404.
Xu X, Liu C, Zheng Y. 3D Tooth Segmentation and Label-ing Using Deep Convolutional Neural Networks. IEEE Trans Vis Comput Graph. 2018;25(7):2336-48.
Tian S, Dai N, Zhang B, Yuan F, Yu Q, Cheng X. Automatic Classification and Segmentation of Teeth on 3D Dental Model Using Hierarchical Deep Learning Networks. IEEE Access. 2019;7:84817-28.
Hatvani J, Horváth A, Michetti J, et al. Deep Learning-Based Super-Resolution Applied to Dental Computed Tomography. IEEE Trans Radiat Plasma Med Sci. 2018;3(2):120-8.
Schwendicke F, Singh T, Lee JH, et al. Artificial Intelli-gence in Dental Research: Checklist for Authors, Re-viewers, Readers. J Dent. 2021;107:103610.
Grischke J, Johannsmeier L, Eich L, Griga L, Haddadin S. Dentronics: Towards Robotics and Artificial Intelligence in Dentistry. Dent Mater. 2020;36(6):765-78.
Kılıc MC, Bayrakdar IS, Çelik Ö, Bilgir E, Orhan K, Aydın OB, Kaplan FA, Sağlam H, Odabaş A, Aslan AF, Yılmaz AB. Artificial Intelligence System for Automatic Decidu-ous Tooth Detection and Numbering in Panoramic Radi-ographs. Dentomaxillofac Radiol. 2021;50(6):20200172.
Shan T, Tay FR, Gu L. Application of Artificial Intelligence in Dentistry. J Dent Res. 2021;100(3):232-44.
Khanna SS, Dhaimade PA. Artificial Intelligence: Trans-forming Dentistry Today. Indian J Basic Appl Med Res. 2017;6(3):161-7.
Thurzo A, Kočiš F, Novák B, Czako L, Varga I. Three-Dimensional Modeling and 3D Printing of Biocompatible Orthodontic Power-Arm Design With Clinical Applica-tion. Appl Sci. 2021;11(20):9693.
Jose AA, Sawhney H, Jose CM, Center GD. Artificial Intel-ligence and Its Applications: Transforming Today’s Den-tistry. Int J Early Child Spec Educ. 2022;14(6):307.
Javaid M, Haleem A, Khan IH, Vaishya R, Vaish A. Ex-tending Capabilities of Artificial Intelligence for Decision-Making and Healthcare Education. Apollo Med. 2020;17(1):53.