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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主要な著者:	Mohammad K. Alam, Mohammad Y. Hajeer, Renad N. Abahussain, Reuof A. Algadri, Dalia M. Alamri, Mohammed E. Rashid
フォーマット:	Artigo
言語:	Inglês
出版事項:	Wolters Kluwer Medknow Publications 2025-12-01
シリーズ:	Journal of Pharmacy and Bioallied Sciences
主題:	ai cephalometrics craniofacial growth growth pattern analysis
オンライン･アクセス:	https://journals.lww.com/10.4103/jpbs.jpbs_1346_25
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