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Under the global COVID-19 crisis, developing robust diagnosis algorithm for COVID-19 using CXR is hampered by the lack of the well-curated COVID-19 data set, although CXR data with other disease are abundant.
2017
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Wang, X., Peng, Y., Lu, L., Lu, Z., Bagheri, M., Summers, R.M.: Chestx-ray8: Hospital-scale chest x-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 2097–2106 (2017)
2017
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2018
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Radford, A., Narasimhan, K., Salimans, T., Sutskever, I.: Improving language understanding by generative pre-training (2018)
2018
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Zech, J.R., Badgeley, M.A., Liu, M., Costa, A.B., Titano, J.J., Oermann, E.K.: Variable generalization performance of a deep learning model to detect pneumonia in chest radiographs: a cross-sectional study. PLoS medicine 15
2018
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Irvin, J., Rajpurkar, P., Ko, M., Yu, Y., Ciurea-Ilcus, S., Chute, C., Marklund, H., Haghgoo, B., Ball, R., Shpanskaya, K., et al.: Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison. In: Proceedings of the AAAI Conference on Artificial Intelligence. vol. 33, pp. 590–597 (2019)
2019
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Apostolopoulos, I.D., Mpesiana, T.A.: Covid-19: automatic detection from x-ray images utilizing transfer learning with convolutional neural networks. Physical and Engineering Sciences in Medicine 43
2020
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Bernheim, A., Mei, X., Huang, M., Yang, Y., Fayad, Z.A., Zhang, N., Diao, K., Lin, B., Zhu, X., Li, K., et al.: Chest ct findings in coronavirus disease-19 (covid-19): relationship to duration of infection. Radiology p. 200463 (2020)
2020
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2020
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Chen, L., Min, Y., Zhang, M., Karbasi, A.: More data can expand the generalization gap between adversarially robust and standard models. In: International Conference on Machine Learning. pp. 1670–1680. PMLR (2020)
2020
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Chen, M., Radford, A., Child, R., Wu, J., Jun, H., Luan, D., Sutskever, I.: Generative pretraining from pixels. In: International Conference on Machine Learning. pp. 1691–1703. PMLR (2020)
2020
Cited alongside, same era.
Chen, T., Kornblith, S., Norouzi, M., Hinton, G.: A simple framework for contrastive learning of visual representations. In: International conference on machine learning. pp. 1597–1607. PMLR (2020)
2020
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Cozzi, D., Albanesi, M., Cavigli, E., Moroni, C., Bindi, A., Luvarà, S., Lucarini, S., Busoni, S., Mazzoni, L.N., Miele, V.: Chest x-ray in new coronavirus disease 2019 (covid-19) infection: findings and correlation with clinical outcome. La radiologia medica 125
2020
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2020
Shi, H., Han, X., Jiang, N., Cao, Y., Alwalid, O., Gu, J., Fan, Y., Zheng, C.: Radiological findings from 81 patients with covid-19 pneumonia in wuhan, china: a descriptive study. The Lancet infectious diseases 20
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2020
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Tahamtan, A., Ardebili, A.: Real-time rt-pcr in covid-19 detection: issues affecting the results. Expert review of molecular diagnostics 20
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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. Scientific Reports 10
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Cited alongside, same era.
2020
Cited alongside, same era.
2020
Cited alongside, same era.
Hu, Y., Jacob, J., Parker, G.J., Hawkes, D.J., Hurst, J.R., Stoyanov, D.: The challenges of deploying artificial intelligence models in a rapidly evolving pandemic. Nature Machine Intelligence 2
2020
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2020
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Ng, K., Poon, B.H., Kiat Puar, T.H., Shan Quah, J.L., Loh, W.J., Wong, Y.J., Tan, T.Y., Raghuram, J.: Covid-19 and the risk to health care workers: a case report. Annals of internal medicine 172
2020
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Oh, Y., Park, S., Ye, J.C.: Deep learning covid-19 features on cxr using limited training data sets. IEEE Transactions on Medical Imaging 39
2020
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Wang, X., Deng, X., Fu, Q., Zhou, Q., Feng, J., Ma, H., Liu, W., Zheng, C.: A weakly-supervised framework for covid-19 classification and lesion localization from chest ct. IEEE transactions on medical imaging 39
2020
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Wong, H.Y.F., Lam, H.Y.S., Fong, A.H.T., Leung, S.T., Chin, T.W.Y., Lo, C.S.Y., Lui, M.M.S., Lee, J.C.Y., Chiu, K.W.H., Chung, T.W.H., et al.: Frequency and distribution of chest radiographic findings in patients positive for covid-19. Radiology 296
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