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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| Auteurs principaux: | , , , , , , , , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2020
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| Accès en ligne: | https://doaj.org/article/f5174425a0734861a7a45f22e97dfdd0 |
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