Evaluating the accuracy of generative artificial intelligence models in dental age estimation based on the Demirjian's method

IntroductionDental age estimation plays a key role in forensic identification, clinical diagnosis, treatment planning, and prognosis in fields such as pediatric dentistry and orthodontics. Large language models (LLM) are increasingly being recognized for their potential applications in Dentistry. Th...

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Main Authors:	Allan Abuabara, Thais Vilalba Paniagua Machado do Nascimento, Seandra Maria Trentini, Angela Mairane Costa Gonçalves, Maria Angélica Hueb de Menezes-Oliveira, Isabela Ribeiro Madalena, Svenja Beisel-Memmert, Christian Kirschneck, Livia Azeredo Alves Antunes, Cristiano Miranda de Araujo, Flares Baratto-Filho, Erika Calvano Küchler
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2025-07-01
Series:	Frontiers in Dental Medicine
Subjects:	artificial intelligence generative artificial intelligence clinical decision-making large language models evidence-based dentistry age determination by teeth
Online Access:	https://www.frontiersin.org/articles/10.3389/fdmed.2025.1634006/full
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Evaluating the accuracy of generative artificial intelligence models in dental age estimation based on the Demirjian's method

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