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A Novel Approach to Apply Different Algorithms to Predict COVID-19 Disease

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Part of the Algorithms for Intelligent Systems book series (AIS)

Abstract

Initially, the COVID-19 pandemic occurred in Wuhan in December 2019 and later it spread throughout the world. Moreover, COVID-19 is a transferable infection, which has been recently treated with vaccination and medicines. Washing hands, wearing a face mask, and social distancing are the most important factors that assist in reducing the transmission of the infection. In addition to clinical investigations, PC-assisted examinations are now often regulated for analyzing the COVID-19 phase. During this test, computer-based intelligence methods are used efficiently. In this study, we employed different algorithms to anticipate and analyze the COVID-19 affected individuals every day. As a result, the number of daily COVID-19 situations were successfully analyzed by using different types of algorithms.

Keywords

  • COVID-19
  • Classification
  • Algorithmic comparison
  • Intelligence
  • Prediction
  • Analysis

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  • DOI: 10.1007/978-981-16-6460-1_6
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Mahesh, U., Jason, B.S., Nishitha, S.N.T., Kiran, J.S. (2022). A Novel Approach to Apply Different Algorithms to Predict COVID-19 Disease. In: Jacob, I.J., Kolandapalayam Shanmugam, S., Bestak, R. (eds) Data Intelligence and Cognitive Informatics. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-6460-1_6

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