Leveraging Data Science to Combat COVID-19: A Comprehensive Review
Article Properties
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DOI (url)
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Publication Date2020/08/01
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Indian UGC (journal)
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Refrences243
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Citations4
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Siddique Latif ORCID (unauthenticated)
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Muhammad Usman ORCID (unauthenticated)
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Sanaullah Manzoor
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Waleed Iqbal
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Junaid Qadir ORCID (unauthenticated)
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Gareth Tyson
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Ignacio Castro ORCID (unauthenticated)
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Adeel Razi ORCID (unauthenticated)
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Maged N. Kamel Boulos ORCID (unauthenticated)
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Adrian Weller ORCID (unauthenticated)
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Jon Crowcroft ORCID (unauthenticated)
Cite
Latif, Siddique, et al. “Leveraging Data Science to Combat COVID-19: A Comprehensive Review”. IEEE Transactions on Artificial Intelligence, vol. 1, no. 1, 2020, pp. 85-103, https://doi.org/10.1109/tai.2020.3020521.
Latif, S., Usman, M., Manzoor, S., Iqbal, W., Qadir, J., Tyson, G., Castro, I., Razi, A., Boulos, M. N. K., Weller, A., & Crowcroft, J. (2020). Leveraging Data Science to Combat COVID-19: A Comprehensive Review. IEEE Transactions on Artificial Intelligence, 1(1), 85-103. https://doi.org/10.1109/tai.2020.3020521
Latif, Siddique, Muhammad Usman, Sanaullah Manzoor, Waleed Iqbal, Junaid Qadir, Gareth Tyson, Ignacio Castro, et al. “Leveraging Data Science to Combat COVID-19: A Comprehensive Review”. IEEE Transactions on Artificial Intelligence 1, no. 1 (2020): 85-103. https://doi.org/10.1109/tai.2020.3020521.
Latif S, Usman M, Manzoor S, Iqbal W, Qadir J, Tyson G, et al. Leveraging Data Science to Combat COVID-19: A Comprehensive Review. IEEE Transactions on Artificial Intelligence. 2020;1(1):85-103.
Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Keep up with the latest coronavirus research | Nature |
| 149 | 2020 |
| A novel coronavirus from patients with pneumonia in China, 2019 | 2020 | |||
Using artificial intelligence to read chest radiographs for tuberculosis detection: A multi-site evaluation of the diagnostic accuracy of three deep learning systems | Scientific Reports |
| 134 | 2019 |
| How 5G Wireless (and Concomitant Technologies) Will Revolutionize Healthcare? | Future Internet |
| 83 | 2017 |
Modeling infectious disease dynamics in the complex landscape of global health | Science |
| 376 | 2015 |
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| From assistive technology to the backbone: the impact of blockchain in manufacturing | Evolutionary Intelligence |
| 2023 | |
| Short- and Long-Term Predicted and Witnessed Consequences of Digital Surveillance During the COVID-19 Pandemic: A Scoping Review (Preprint) | JMIR Public Health and Surveillance |
| 2023 | |
Combating COVID-19 Using Generative Adversarial Networks and Artificial Intelligence for Medical Images: Scoping Review | JMIR Medical Informatics |
| 3 | 2022 |
D2-CovidNet: A Deep Learning Model for COVID-19 Detection in Chest X-Ray Images | Computational Intelligence and Neuroscience |
| 4 | 2021 |
Citations Analysis
The category
Medicine: Medicine (General) 2
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled D2-CovidNet: A Deep Learning Model for COVID-19 Detection in Chest X-Ray Images and was published in 2021. The most recent citation comes from a 2023 study titled Short- and Long-Term Predicted and Witnessed Consequences of Digital Surveillance During the COVID-19 Pandemic: A Scoping Review (Preprint). This article reached its peak citation in 2023, with 2 citations. It has been cited in 4 different journals, 50% of which are open access. Among related journals, the JMIR Public Health and Surveillance cited this research the most, with 1 citations. The chart below illustrates the annual citation trends for this article.