Abstract
A pandemic has broken out throughout the world since December 2019 and later it has been named COVID-19. The flow of normal life has collapsed due to this pandemic, especially in the economic, public health, and education sectors. The number of infected people is increasing daily. So, the identification of COVID-19 patients is a crying need in the health sector to stop the spread of this virus. Recently, Machine Learning algorithms have shown fascinating results in the prediction of medical data. In this study, we have proposed an approach to predict COVID-19 on human genomic data using the CpG Island feature and the newly introduced AT-CG feature by Machine Learning algorithms. Our proposed system produces an impressive result of the highest 99.91% accuracy on the Naïve Bayes algorithm.
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Manik, M.H., Habib, M., Ahmed, T. (2023). Machine Learning Algorithms on COVID-19 Prediction Using CpG Island and AT-CG Feature on Human Genomic Data. In: Satu, M.S., Moni, M.A., Kaiser, M.S., Arefin, M.S. (eds) Machine Intelligence and Emerging Technologies. MIET 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 491. Springer, Cham. https://doi.org/10.1007/978-3-031-34622-4_59
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DOI: https://doi.org/10.1007/978-3-031-34622-4_59
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