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Sex determination from lateral cephalometric radiographs using an automated deep learning convolutional neural network
PURPOSE: Despite the proliferation of numerous morphometric and anthropometric methods for sex identification based on linear, angular, and regional measurements of various parts of the body, these methods are subject to error due to the observer’s knowledge and expertise. This study aimed to explor...
Autores principales: | Khazaei, Maryam, Mollabashi, Vahid, Khotanlou, Hassan, Farhadian, Maryam |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Academy of Oral and Maxillofacial Radiology
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9530293/ https://www.ncbi.nlm.nih.gov/pubmed/36238705 http://dx.doi.org/10.5624/isd.20220016 |
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