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The Coronavirus Disease 2019 (COVID-19) has spread globally and caused serious damage.
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Heshui Shi, Xiaoyu Han, Nanchuan Jiang, Yukun Cao, Osamah Alwalid, Jin Gu, Yanqing Fan, Chuansheng Zheng,Radiological findings from 81 patients with COVID-19 pneumonia in Wuhan, China: a descriptive study, The Lancet Infectious Diseases, 2020, Pages 425-434
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Shervin Minaee, Rahele Kafieh, Milan Sonka, Shakib Yazdani, Ghazaleh Jamalipour Soufi, Deep-COVID: Predicting COVID-19 from chest X-ray images using deep transfer learning, Medical Image Analysis, Volume 65, 2020
Wang, L., Lin, Z.Q.,Wong, A. COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest X-ray images. Sci Rep 10, 19549 (2020)
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S. Basu, S. Mitra and N. Saha, Deep Learning for Screening COVID-19 using Chest X-Ray Images,2020 IEEE Symposium Series on Computational Intelligence (SSCI), 2020, pp. 2521-2527
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Jain, R., Gupta, M., Taneja, S. et al, Deep learning based detection and analysis of COVID-19 on chest X-ray images. Appl Intell 51, 1690–1700 (2021)
2021
Closest in time.
Akhloufi, Moulay A. and Chetoui, Mohamed, Chest XR COVID-19 detection,https://cxr-covid19.grand-challenge.org/,August,2021
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2020
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Asif Iqbal Khan, Junaid Latief Shah, Mohammad Mudasir Bhat, CoroNet: A deep neural network for detection and diagnosis of COVID-19 from chest x-ray images, Computer Methods and Programs in Biomedicine, Volume 196,2020
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2021
Closest in time.