Artificial Intelligence in Orthodontics: A Scoping Review of Methods and Applications
Yodhathai Satravaha, Chaiyapol Chaweewannakorn, Kawin Sipiyaruk, Supatchai Boonpratham, Ard Likitkulthanaporn, Supakit Peanchitlertkajorn, Zaw Htet AungABSTRACT
The rapid integration of artificial intelligence (AI) into orthodontics raises important questions about which methods are being applied, how they are being validated, and what barriers remain to clinical implementation. This study was conducted to inform orthodontic practitioners, researchers, and educators about the possibilities that AI could bring to orthodontics and to emphasise the need for increased collaboration among experts. The literature search was performed across four databases: PubMed, Scopus, Embase, ProQuest Dissertations & Theses Global (PQDT). All types of clinical studies involving the design and implementation of AI in all aspects of orthodontics published from January 2000 to August 2024 were included in this review. The search identified 1917 articles from the four databases (PubMed = 455, Scopus = 668, Embase = 554, and PQDT = 240). After 566 duplicates were removed, 1351 titles and abstracts were screened. Finally, 110 full text articles were included in this scoping review focusing on the following areas: diagnosis, treatment planning, practice management, evaluation of orthodontic devices, and orthodontic education. A thorough search across databases and relevant sources was conducted to gather a comprehensive understanding of how AI impacted orthodontics research. This scoping review carefully examined the existing literature on the applications of AI across various aspects of orthodontics. The findings provide insights into the utilisation of AI in this field, identify challenges faced when integrating AI‐driven methods and uncover gaps in the knowledge that require further research.