Current limitations to identify COVID-19 using artificial intelligence with chest X-ray imaging
Author:
Publisher
Springer Science and Business Media LLC
Subject
Biomedical Engineering,Applied Microbiology and Biotechnology,Bioengineering,Biotechnology
Link
http://link.springer.com/content/pdf/10.1007/s12553-021-00520-2.pdf
Reference87 articles.
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2. Salman S, Salem ML. Routine childhood immunization may protect against COVID-19. Med Hypotheses. 2020;140:109689. https://doi.org/10.1016/j.mehy.2020.109689.
3. Xie M, Chen Q. Insight into 2019 novel coronavirus — An updated interim review and lessons from SARS-CoV and MERS-CoV. Int J Infect Dis. 2020;94:119–24. https://doi.org/10.1016/j.ijid.2020.03.071.
4. Liu R, et al. Positive rate of RT-PCR detection of SARS-CoV-2 infection in 4880 cases from one hospital in Wuhan, China, from Jan to Feb 2020. Clin Chim Acta. 2020;505:172–5. https://doi.org/10.1016/j.cca.2020.03.009.
5. Narayan Das N, Kumar N, Kaur M, Kumar V, Singh D. Automated deep transfer learning-based approach for detection of COVID-19 infection in chest X-rays. IRBM, 2020. https://doi.org/10.1016/j.irbm.2020.07.001.
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