Artificial Intelligence Applications in Orthodontics
This manuscript describes strategies for assessment of precision of several diagnostic artificial intelligence (AI) tools in orthodontics, available open-source image analysis platforms, as well as the use of three-dimensional (3D) surface models and superimpositions. The advances described in this manuscript present perspectives on the controversies of whether AI is smarter than clinicians and may replace human clinical decisions. A thorough orthodontic diagnosis requires comprehensive 3D analysis of the interrelationships among the dentition, craniofacial skeleton and soft tissues. Forecasts have indicated that 3D printing technology will provide more than 60% of all dental treatment needs by 2025, and orthodontic companies as well as remote monitoring companies are already using AI technology, being it essential that the clinicians are prepared and knowledgeable with the technology advances now available. The AI applications in orthodontics rely on the implementation into diagnostic image records, data analysis for clinical practice and research applications. Continuous training and validation of the AI orthodontic image tools are essential for improving the performance and generalizability of these methods.
Authors
- Luc Anchling
- Maxime Gillot (ORCID: https://orcid.org/0000-0003-1887-6417)
- Jonas Bianchi (ORCID: https://orcid.org/0000-0002-3749-0918)
- Camila Massaro (ORCID: https://orcid.org/0000-0001-6011-7946)
- Arón Aliaga-Del Castillo (ORCID: https://orcid.org/0000-0003-3963-1742)
- Antônio Carlos de Oliveira Ruellas (ORCID: https://orcid.org/0000-0001-7973-9286)
- Daniela Gamba Garib (ORCID: https://orcid.org/0000-0002-2449-1620)
- Marília Yatabe (ORCID: https://orcid.org/0000-0002-8748-6714)
- Selene Barone (ORCID: https://orcid.org/0000-0002-0701-2675)
- Felícia Miranda (ORCID: https://orcid.org/0000-0002-4015-0623)
- Karine Evangelista (ORCID: https://orcid.org/0000-0003-0258-9739)
- Lucía Cevidanes (ORCID: https://orcid.org/0000-0001-9786-2253)
- Nathan Hutin
- Baptiste Baquero
- Najla Al Turkestani (ORCID: https://orcid.org/0000-0002-7650-3638)
- Marcela Gurgel (ORCID: https://orcid.org/0000-0001-9978-0542)
- Hina Shah (ORCID: https://orcid.org/0000-0001-7050-5205)
- Juan Carlos Prieto (ORCID: https://orcid.org/0000-0002-3778-9098)
- Yanjie Huang (ORCID: https://orcid.org/0000-0002-9536-9622)
Institutions
- University of North Carolina at Chapel Hill (US)
Publication Details
- Journal
- UNC Libraries
- Published
- 2025-03-21
- DOI
- https://doi.org/10.17615/dkcw-ky46
- Citations
- 1
- Primary Topic
- Dental Radiography and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.79
Funders
- National Institute of Dental and Craniofacial Research