Machine Learning and Deep Learning Approaches to Analyze and Detect COVID-19: A Review-Reference-Cited by-同舟云学术

Machine Learning and Deep Learning Approaches to Analyze and Detect COVID-19: A Review

Published:2021-04-20 Issue:3 Volume:2 Page:
ISSN:2662-995X
Container-title:SN Computer Science
language:en
Short-container-title:SN COMPUT. SCI.

Author:

Aishwarya T.^ORCID,Ravi Kumar V.^ORCID

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s42979-021-00605-9.pdf

Reference18 articles.

1. Wang et al. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus– infected pneumonia in Wuhan, China. In: Jama, p. in Press, 2020.

2. Chan JF, et al. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. Lancet. 2020;395(10223):514–23.

3. Zu ZY et al. Coronavirus disease 2019 (COVID-19): a perspective from China. In: Radiology, p. 200490 2020.

4. Ophir G et al. Rapid AI development cycle for the coronavirus (COVID-19) pandemic: initial results for automated detection & patient monitoring using deep learning CT image analysis. In: Radiology- Artificial Intelligence, arXiv:2003.05037 [eess.IV] 2020.

5. Md Zahangir A et al. COVID_MTNet: COVID-19 detection with multi-task deep learning approaches. In: arXiv:2004.03747 [eess.IV], 2020.

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