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. 2020 Sep 22;7(1):235–247. doi: 10.1007/s40747-020-00199-4

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© The Author(s) 2020

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 6 — Final recommended deep X-ray image classifiers for detecting COVID-19, viral and bacterial pneumonia diseases using VGG16, ReseNet50V2 and DenseNet169 models, respectively (right). The corresponding accuracy and loss curves with resulted confusion matrix are linked to each image classifier (left)