Articles Tập 67 Số CĐ16 11/11/2026

ACCURACY AND RELIABILITY OF WEB-BASED ARTIFICIAL INTELLIGENCE PLATFORMS FOR CERVICAL VERTEBRAL MATURATION ASSESSMENT

Ta Thi Thu Hang, Dao Thi Hang Nga
DOI: 10.52163/yhc.v67iCD16.7057
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Abstract

Objective: This study aimed to evaluate the performance of artificial intelligence (AI)-based platforms in assessing cervical vertebral maturation (CVM).

Methods: This retrospective cross-sectional study included 350 lateral cephalograms from patients aged 5-18 years who attended the Center for High-Tech Dental Care, Hanoi Medical University, between January 2019 and June 2025. CVM staging was performed using two AI-based platforms, with each assessment repeated after a two-week interval. CVM stages determined by the investigator according to the Baccetti et al.(2005) method served as the reference standard. Reliability was assessed based on intra-platform repeatability. Accuracy was evaluated using exact agreement rates with the reference standard, quantified by weighted kappa coefficients.

Results: Both AI platforms demonstrated 100% repeatability between the two assessments, indicating excellent reliability and consistency. Although exact agreement with the reference standard was relatively low (42,3% for iOrtho and 34,6% for Vincismile), agreement based on weighted kappa was very good for iOrtho (k=0,82) and good for Vincismile (k=0,80) Conclusion: Both web-based AI platforms demonstrated perfect repeatability and good to very good agreement with the reference standard for CVM assessment. AI may serve as a useful adjunct to clinical evaluation; however, its results should be interpreted in conjunction with the clinician’s own assessment.

Keywords
artificial intelligence, cervical vertebral maturation, cephalometrics.
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