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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Bibliografiske detaljer

Principais autores:	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:	Artigo
Sprog:	Inglês
Udgivet:	Frontiers Media S.A. 2025-07-01
Serier:	Frontiers in Dental Medicine
Fag:	artificial intelligence generative artificial intelligence clinical decision-making large language models evidence-based dentistry age determination by teeth
Online adgang:	https://www.frontiersin.org/articles/10.3389/fdmed.2025.1634006/full
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