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COVID-19 Risk Assessment Using the C4.5 Algorithm

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Computational Intelligence Techniques for Combating COVID-19

Part of the book series: EAI/Springer Innovations in Communication and Computing ((EAISICC))

Abstract

The number of confirmed cases of COVID-19 is increasing exponentially day by day across the world because of its super spreading nature. It was started in China and took a very less time to spread all over the globe. Due to its mortality rate, spreading nature, and unavailability of proper medicine and vaccination, it is declared as a pandemic by the World Health Organization (WHO) in March 2020. In this crisis time of the COVID-19 outbreak, technologists try to smooth the lives by minimizing the infection rate and facilitating in-time quality treatment. In this work, we collected the world data of COVID-19 cases in terms of confirmed, recovery, active, and death and provided visualization. We have also tried to find the patient’s risk level in terms of high, medium, and low by analyzing the patient’s symptoms and previous health histories such as high blood pressure, cardiac disease, diabetes, kidney issues, and others. We applied the C4.5 machine learning (ML) classifier to the considered dataset after preprocessing for risk assessment. The results obtained from the study indicate that the algorithm helps in achieving 75% accuracy.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Rama Devi Women’s University, Bhubaneswar, Odisha, India

    Sarmistha Nanda, Chhabi Rani Panigrahi & Bibudhendu Pati

  2. School of Management (IT), Birla Global University, Bhubaneswar, Odisha, India

    Mamata Rath

  3. Department of Computer Science & Information Engineering, Providence University, Taichung, Taiwan

    Tien-Hsiung Weng

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  1. Sarmistha Nanda
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  2. Chhabi Rani Panigrahi
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  3. Bibudhendu Pati
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  4. Mamata Rath
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  5. Tien-Hsiung Weng
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Editors and Affiliations

  1. LBEF Campus, Kathmandu Nepal; (In Academic Collaboration with Asia Pacific University of Technology & Innovation), Kuala Lumpur, Malaysia

    Sandeep Kautish

  2. Taoyuan Campus, National Taipei University of Business, Taoyuan, Taiwan

    Sheng-Lung Peng

  3. Faculty of Computer Science and Mathematics, Department of Computer Science, University of Kufa, Najaf, Iraq

    Ahmed J. Obaid

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Nanda, S., Panigrahi, C.R., Pati, B., Rath, M., Weng, TH. (2021). COVID-19 Risk Assessment Using the C4.5 Algorithm. In: Kautish, S., Peng, SL., Obaid, A.J. (eds) Computational Intelligence Techniques for Combating COVID-19. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-68936-0_4

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  • DOI: https://doi.org/10.1007/978-3-030-68936-0_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-68935-3

  • Online ISBN: 978-3-030-68936-0

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