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Review
. 2023 Dec 15;13(24):3677.
doi: 10.3390/diagnostics13243677.

Artificial Intelligence and Its Clinical Applications in Orthodontics: A Systematic Review

Gianna Dipalma  1 , Alessio Danilo Inchingolo  1 , Angelo Michele Inchingolo  1 , Fabio Piras  1 , Vincenzo Carpentiere  1 , Grazia Garofoli  1 , Daniela Azzollini  1 , Merigrazia Campanelli  1 , Gregorio Paduanelli  1 , Andrea Palermo  2 , Francesco Inchingolo  1
Affiliations
Review

Artificial Intelligence and Its Clinical Applications in Orthodontics: A Systematic Review

Gianna Dipalma et al. Diagnostics (Basel). .

Abstract

This review aims to analyze different strategies that make use of artificial intelligence to enhance diagnosis, treatment planning, and monitoring in orthodontics. Orthodontics has seen significant technological advancements with the introduction of digital equipment, including cone beam computed tomography, intraoral scanners, and software coupled to these devices. The use of deep learning in software has sped up image processing processes. Deep learning is an artificial intelligence technology that trains computers to analyze data like the human brain does. Deep learning models are capable of recognizing complex patterns in photos, text, audio, and other data to generate accurate information and predictions.

Materials and methods: Pubmed, Scopus, and Web of Science were used to discover publications from 1 January 2013 to 18 October 2023 that matched our topic. A comparison of various artificial intelligence applications in orthodontics was generated.

Results: A final number of 33 studies were included in the review for qualitative analysis.

Conclusions: These studies demonstrate the effectiveness of AI in enhancing orthodontic diagnosis, treatment planning, and assessment. A lot of articles emphasize the integration of artificial intelligence into orthodontics and its potential to revolutionize treatment monitoring, evaluation, and patient outcomes.

Keywords: artificial intelligence; deep learning; diagnosis; machine learning; orthodontics; treatment monitoring; treatment planning.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Example of the identification of cephalometric points by AI from a lateral–lateral teleradiographic image required for orthodontic purposes.
Figure 2
Figure 2
PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flowchart of the literature search and article inclusion process.
Figure 3
Figure 3
Quality assessment of bias [5,31,32,33,34,35,37,38,39,40,41,42,43,44,46,47,49,51,53,54,59,62,63,64,65,66,67,68,70,72].
See this image and copyright information in PMC

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