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Comparative Evaluation of Craniofacial Growth Patterns Using AI-Driven Longitudinal Cephalometric Superimpositions in Adolescents

Background: Accurate analysis of craniofacial growth is essential for individualized orthodontic treatment planning. Traditional cephalometric methods often rely on manual tracing, which can be time-consuming and subject to interobserver variability. Recent advances in artificial intelligence (AI) o...

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Principais autores: Mohammad K. Alam, Mohammad Y. Hajeer, Renad N. Abahussain, Reuof A. Algadri, Dalia M. Alamri, Mohammed E. Rashid
Formato: Artigo
Idioma:Inglês
Publicado em: Wolters Kluwer Medknow Publications 2025-12-01
coleção:Journal of Pharmacy and Bioallied Sciences
Assuntos:
ai cephalometrics
craniofacial growth
growth pattern analysis
Acesso em linha:https://journals.lww.com/10.4103/jpbs.jpbs_1346_25
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