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Applications of artificial intelligence and machine learning in orthodontics: a scoping review

Authors
  • Bichu, Yashodhan M.1
  • Hansa, Ismaeel2
  • Bichu, Aditi Y.1
  • Premjani, Pratik3
  • Flores-Mir, Carlos4
  • Vaid, Nikhilesh R.5
  • 1 1 , Abu Dhabi (United Arab Emirates)
  • 2 2 , Durban (South Africa)
  • 3 3 , Dubai (United Arab Emirates)
  • 4 University of Alberta, Edmonton, Alberta, Canada , Edmonton (Canada)
  • 5 European University College, Dubai, United Arab Emirates , Dubai (United Arab Emirates)
Type
Published Article
Journal
Progress in Orthodontics
Publisher
Springer Berlin Heidelberg
Publication Date
Jul 05, 2021
Volume
22
Issue
1
Identifiers
DOI: 10.1186/s40510-021-00361-9
Source
Springer Nature
Keywords
Disciplines
  • Review
License
Green

Abstract

IntroductionThis scoping review aims to provide an overview of the existing evidence on the use of artificial intelligence (AI) and machine learning (ML) in orthodontics, its translation into clinical practice, and what limitations do exist that have precluded their envisioned application.MethodsA scoping review of the literature was carried out following the PRISMA-ScR guidelines. PubMed was searched until July 2020.ResultsSixty-two articles fulfilled the inclusion criteria. A total of 43 out of the 62 studies (69.35%) were published this last decade. The majority of these studies were from the USA (11), followed by South Korea (9) and China (7). The number of studies published in non-orthodontic journals (36) was more extensive than in orthodontic journals (26). Artificial Neural Networks (ANNs) were found to be the most commonly utilized AI/ML algorithm (13 studies), followed by Convolutional Neural Networks (CNNs), Support Vector Machine (SVM) (9 studies each), and regression (8 studies). The most commonly studied domains were diagnosis and treatment planning—either broad-based or specific (33), automated anatomic landmark detection and/or analyses (19), assessment of growth and development (4), and evaluation of treatment outcomes (2). The different characteristics and distribution of these studies have been displayed and elucidated upon therein.ConclusionThis scoping review suggests that there has been an exponential increase in the number of studies involving various orthodontic applications of AI and ML. The most commonly studied domains were diagnosis and treatment planning, automated anatomic landmark detection and/or analyses, and growth and development assessment.

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