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# COVID-CXNet
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[ ![ license] ( https://img.shields.io/github/license/mashape/apistatus.svg?style=flat-square )] ( https://github.com/armiro/COVID-CXNet/blob/master/LICENSE )
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- ![ license] ( https://img.shields.io/badge/development-100%25-yellow?style=flat-square )
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- [ ![ license] ( https://img.shields.io/badge/preprint-arxiv-b31b1b?style=flat-square )] ( https://arxiv.org/abs/2006.13807 )
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- [ ![ license] ( https://img.shields.io/badge/doi-10.1007/s11042--022--12156--z-1e8bc3?style=flat-square )] ( https://link.springer.com/article/10.1007/s11042-022-12156-z )
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+ ![ development] ( https://img.shields.io/badge/development-100%25-yellow?style=flat-square )
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+ [ ![ preprint] ( https://img.shields.io/badge/preprint-arxiv-b31b1b?style=flat-square )] ( https://arxiv.org/abs/2006.13807 )
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+ [ ![ paper doi] ( https://img.shields.io/badge/doi-10.1007/s11042--022--12156--z-1e8bc3?style=flat-square )] ( https://link.springer.com/article/10.1007/s11042-022-12156-z )
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+ ![ repo size] ( https://img.shields.io/github/repo-size/armiro/COVID-CXNet.svg?style=flat-square&color=9b59b6 )
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Detecting the novel coronavirus pneumonia in frontal chest X-ray images using transfer learning of CheXNet with a focus on Grad-CAM visualiztions.
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