Automated abnormality classification of chest radiographs using deep convolutional neural networks
Abstract As one of the most ubiquitous diagnostic imaging tests in medical practice, chest radiography requires timely reporting of potential findings and diagnosis of diseases in the images. Automated, fast, and reliable detection of diseases based on chest radiography is a critical step in radiolo...
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Autores principales: | Yu-Xing Tang, You-Bao Tang, Yifan Peng, Ke Yan, Mohammadhadi Bagheri, Bernadette A. Redd, Catherine J. Brandon, Zhiyong Lu, Mei Han, Jing Xiao, Ronald M. Summers |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2020
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Materias: | |
Acceso en línea: | https://doaj.org/article/f5174425a0734861a7a45f22e97dfdd0 |
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