Machine learning applications for COVID-19: a state-of-the-art review

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Date
2022-01-01
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Volume Title
Publisher
Elsevier
Abstract
Description
Keywords
Applications, Covid-19, Diagnosis, Forecasting, Machine learning, Survey
Citation
Kamalov, F., Cherukuri, A. K., Sulieman, H., Thabtah, F., & Hossain, A. (2023). Machine learning applications for COVID-19: a state-of-the-art review. In A. K. Tyagi & A. Abraham (Eds.), Data Science for Genomics (pp. 277-289). Academic Press. https://doi.org/10.1016/B978-0-323-98352-5.00010-0
URI
https://doi.org/10.1016/B978-0-323-98352-5.00010-0
 https://hdl.handle.net/20.500.12519/851
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Department of Electrical Engineering