Accuracy of one-step automated orthodontic diagnosis model using a convolutional neural network and lateral cephalogram images with different qualities obtained from nationwide multi-hospitals

OBJECTIVE: The purpose of this study was to investigate the accuracy of one-step automated orthodontic diagnosis of skeletodental discrepancies using a convolutional neural network (CNN) and lateral cephalogram images with different qualities from nationwide multi-hospitals. METHODS: Among 2,174 lat...

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Detalles Bibliográficos
Autores principales: Yim, Sunjin, Kim, Sungchul, Kim, Inhwan, Park, Jae-Woo, Cho, Jin-Hyoung, Hong, Mihee, Kang, Kyung-Hwa, Kim, Minji, Kim, Su-Jung, Kim, Yoon-Ji, Kim, Young Ho, Lim, Sung-Hoon, Sung, Sang Jin, Kim, Namkug, Baek, Seung-Hak
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Association of Orthodontists 2022
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8770967/
https://www.ncbi.nlm.nih.gov/pubmed/35046138
http://dx.doi.org/10.4041/kjod.2022.52.1.3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8770967/
https://www.ncbi.nlm.nih.gov/pubmed/35046138
http://dx.doi.org/10.4041/kjod.2022.52.1.3

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