Automated detection and classification of the proximal humerus fracture by using deep learning algorithm

Background and purpose — We aimed to evaluate the ability of artificial intelligence (a deep learning algorithm) to detect and classify proximal humerus fractures using plain anteroposterior shoulder radiographs. Patients and methods — 1,891 images (1 image per person) of normal shoulders (n = 515)...

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Detalles Bibliográficos
Autores principales: Chung, Seok Won, Han, Seung Seog, Lee, Ji Whan, Oh, Kyung-Soo, Kim, Na Ra, Yoon, Jong Pil, Kim, Joon Yub, Moon, Sung Hoon, Kwon, Jieun, Lee, Hyo-Jin, Noh, Young-Min, Kim, Youngjun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6066766/
https://www.ncbi.nlm.nih.gov/pubmed/29577791
http://dx.doi.org/10.1080/17453674.2018.1453714

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6066766/
https://www.ncbi.nlm.nih.gov/pubmed/29577791
http://dx.doi.org/10.1080/17453674.2018.1453714

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