Artificial intelligence for skeletal classification in orthodontics: A systematic review and meta-analysis of lateral cephalometric studies

Mahmood Dashti; Farshad Khosraviani; Sara Esmaeili; Niloofar Ghadimi; Kaan Orhan; Atieh Meyari; Zohaib Khurshid; Falk Schwendicke

doi:10.1016/j.jtumed.2026.06.003

July 1, 2026Journal of Taibah University Medical SciencesOpen Access

Artificial intelligence for skeletal classification in orthodontics: A systematic review and meta-analysis of lateral cephalometric studies

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Key Points

This review aims to evaluate the diagnostic performance of artificial intelligence in structural classification based on lateral cephalometric images.
Conducted a systematic search in PubMed, Embase, Scopus, and Web of Science according to PRISMA guidelines.
Included studies applying AI to classify skeletal relationships into classes I, II, and III based on lateral cephalometric images.
Performed a meta-analysis with random effects model and assessed bias using QUADAS-2 tool.
Four studies met inclusion criteria, with a total effective sample size of 2,743 and three included in quantitative analysis.
Overall multi-class classification performance yielded a sensitivity of 87.0% (95% CI: 85.6–88.4) and specificity of 91.1% (95% CI: 87.3–94.9).
DenseNet models outperformed others, while Swin-T showed the weakest performance; bias risk ranged from low to moderate.

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Implication

Systematic review assesses diagnostic performance of AI in structural classification using cephalometric images, suggesting further research is needed.

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Dashti et al. (2026) studied this question.

synapsesocial.com/papers/6a48a29489561a0c2d78d162 https://doi.org/10.1016/j.jtumed.2026.06.003

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Artificial intelligence for skeletal classification in orthodontics: A systematic review and meta-analysis of lateral cephalometric studies

Key Points

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Abstract

Discussion

Cite This Study

Artificial intelligence for skeletal classification in orthodontics: A systematic review and meta-analysis of lateral cephalometric studies

Key Points

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Implication

Abstract

Discussion

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