Development and validation of a deep learning-based model to distinguish acetabular fractures on pelvic anteroposterior radiographs

Objective: To develop and test a deep learning (DL) model to distinguish acetabular fractures (AFs) on pelvic anteroposterior radiographs (PARs) and compare its performance to that of clinicians. Materials and methods: A total of 1,120 patients from a big level-I trauma center were enrolled and allo...

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Detalles Bibliográficos
Autores principales: Ye, Pengyu, Li, Sihe, Wang, Zhongzheng, Tian, Siyu, Luo, Yi, Wu, Zhanyong, Zhuang, Yan, Zhang, Yingze, Grzegorzek, Marcin, Hou, Zhiyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Physiology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10176114/
https://www.ncbi.nlm.nih.gov/pubmed/37187961
http://dx.doi.org/10.3389/fphys.2023.1146910

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10176114/
https://www.ncbi.nlm.nih.gov/pubmed/37187961
http://dx.doi.org/10.3389/fphys.2023.1146910

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