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Age group prediction with panoramic radiomorphometric parameters using machine learning algorithms

The aim of this study is to investigate the relationship of 18 radiomorphometric parameters of panoramic radiographs based on age, and to estimate the age group of people with permanent dentition in a non-invasive, comprehensive, and accurate manner using five machine learning algorithms. For the st...

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Detalles Bibliográficos
Autores principales: Lee, Yeon-Hee, Won, Jong Hyun, Auh, Q.-Schick, Noh, Yung-Kyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9271070/
https://www.ncbi.nlm.nih.gov/pubmed/35810213
http://dx.doi.org/10.1038/s41598-022-15691-9