Leveraging Data Science to Combat COVID-19: A Comprehensive Review-Reference-Cited by-同舟云学术

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Leveraging Data Science to Combat COVID-19: A Comprehensive Review

Published:2020-08 Issue:1 Volume:1 Page:85-103
ISSN:2691-4581
Container-title:IEEE Transactions on Artificial Intelligence
language:
Short-container-title:IEEE Trans. Artif. Intell.

Author:

Latif Siddique^ORCID,Usman Muhammad^ORCID,Manzoor Sanaullah,Iqbal Waleed,Qadir Junaid^ORCID,Tyson Gareth,Castro Ignacio^ORCID,Razi Adeel^ORCID,Boulos Maged N. Kamel^ORCID,Weller Adrian^ORCID,Crowcroft Jon^ORCID

Funder

David MacKay Newton

Alan Turing Institute

Leverhulme Trust

ARC

National Health and Medical Research Council

Wellcome Trust

Engineering and Physical Sciences Research Council

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

https://ieeexplore.ieee.org/ielam/9078688/9271839/9184922-aam.pdf

Cited by 129 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. COVID-19 Modeling: A Review;ACM Computing Surveys;2024-08-05

2. Towards unsupervised radiograph clustering for COVID-19: The use of graph-based multi-view clustering;Engineering Applications of Artificial Intelligence;2024-07

3. A COVID-19 CXR Image Recognition Method Based on Deep Transfer Learning;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

4. Short- and Long-Term Predicted and Witnessed Consequences of Digital Surveillance During the COVID-19 Pandemic: Scoping Review;JMIR Public Health and Surveillance;2024-05-24

5. SoK: Privacy-Preserving Data Synthesis;2024 IEEE Symposium on Security and Privacy (SP);2024-05-19

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