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Artificial Intelligence Applications in Orthodontics

Authors :
Felicia Miranda
Selene Barone
Maxime Gillot
Baptiste Baquero
Luc Anchling
Nathan Hutin
Marcela Gurgel
Najla Al Turkestani
Yanjie Huang
Camila Massaro
Daniela Garib
Antonio Ruellas
Karine Evangelista
Aron Aliaga-Del Castillo
Marilia Yatabe
Hina Shah
Jonas Bianchi
Juan Carlos Prieto
Lucia Cevidanes
Source :
Journal of the California Dental Association, Vol 51, Iss 1 (2023)
Publication Year :
2023
Publisher :
Taylor & Francis Group, 2023.

Abstract

ABSTRACTObjective 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.Results 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.Conclusions 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.

Details

Language :
English
ISSN :
19424396
Volume :
51
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Journal of the California Dental Association
Publication Type :
Academic Journal
Accession number :
edsdoj.faf3257abd6a4efca7439a85376de75c
Document Type :
article
Full Text :
https://doi.org/10.1080/19424396.2023.2195585