Open Access
E3S Web Conf.
Volume 271, 2021
2021 2nd International Academic Conference on Energy Conservation, Environmental Protection and Energy Science (ICEPE 2021)
Article Number 01039
Number of page(s) 5
Section Energy Development and Utilization and Energy Storage Technology Application
Published online 15 June 2021
  1. Novel Coronavirus Pneumonia Tracking[EB/OL]. (2020) [Google Scholar]
  2. National Health Commission of the People's Republie of China [EB/OL]. (2020) [Google Scholar]
  3. National Administration of Traditional Chinese Medicine [EB/OL]. (2020) [Google Scholar]
  4. W. Guan, Z. Ni, Y. Hu, W. Liang, C. Ou, J. He, L. Liu, H. Shan, C. Lei, and D. Hui, “Clinical characteristics of coronavirus disease 2019 in China,” New England journal of medicine, 382, 1708–1720 (2020) [CrossRef] [Google Scholar]
  5. F. Wu, S. Zhao, B. Yu, Y. Chen, W. Wang, Z. Song, Y. Hu, Z. Tao, J. Tian, and Y. Pei, “A new coronavirus associated with human respiratory disease in China,” Nature, 579, 265–269 (2020) [CrossRef] [PubMed] [Google Scholar]
  6. Ying Song, Shuangjia Zheng, Liang Li, Xiang Zhang, et al. Deep learning Enables Accurate Diagnosis of Novel Coronavirus (COVID-19) with CT images. medRxiv. (2020) [Google Scholar]
  7. Z. Feng, Q. Yu, S. Yao, and L. Luo, “Early Prediction of Disease Progression in 2019 Novel Coronavirus Pneumonia Patients Outside Wuhan with CT and Clinical Characteristics,” medRxiv, (2020) [Google Scholar]
  8. F. Shan, Y. Gao, J. Wang, W. Shi, N. Shi, M. Han, Z. Xue, D. Shen, and Y. Shi, “Lung infection quantification of COVID-19 in CT images with deep learning,” arXiv preprint arXiv:2003.04655, (2020) [Google Scholar]
  9. Y. Wang, M. Hu, Q. Li, X. Zhang, G. Zhai, and N. Yao, “Abnormal respiratory patterns classifier may contribute to large-scale screening of people infected with COVID-19 in an accurate and unobtrusive manner,” arXivpreprint arXiv:2002.05534, (2020) [Google Scholar]
  10. L. Yan, H. Zhang, Y. Xiao, M. Wang, Y. Guo, C. Sun, X. Tang, L. Jing, S. Li, and M. Zhang, “Prediction of criticality in patients with severe Covid-19 infection using three clinical features: a machine learning-based prognostic model with clinical data in Wuhan,” MedRxiv, (2020) [Google Scholar]
  11. S. Wang, B. Kang, J. Ma, and X. Zeng, “A deep learning algorithm using CT images to screen for Corona Virus Disease (COVID-19),” medRxiv, (2020) [Google Scholar]
  12. C. Zheng, X. Deng, and Q. Fu, “Deep Learning-based Detection for COVID-19 from Chest CT using Weak Label,” medRxiv, (2020) [Google Scholar]
  13. A. Abbas, M. Abdelsamea, and M. Gaber, “Classification of COVID-19 in chest X-ray images using DeTraC deep convolutional neural network,” medRxiv, (2020) [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.