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Current Artificial Intelligence (AI) Techniques, Challenges, and Approaches in Controlling and Fighting COVID-19: A Review

Author

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  • Umar Albalawi

    (Faculty of Computing and Information Technology, University of Tabuk, KSA, Tabuk 71491, Saudi Arabia
    Industrial Innovation and Robotics Center, University of Tabuk, KSA, Tabuk 71491, Saudi Arabia)

  • Mohammed Mustafa

    (Faculty of Computing and Information Technology, University of Tabuk, KSA, Tabuk 71491, Saudi Arabia
    Industrial Innovation and Robotics Center, University of Tabuk, KSA, Tabuk 71491, Saudi Arabia)

Abstract

SARS-CoV-2 (COVID-19) has been one of the worst global health crises in the 21st century. The currently available rollout vaccines are not 100% effective for COVID-19 due to the evolving nature of the virus. There is a real need for a concerted effort to fight the virus, and research from diverse fields must contribute. Artificial intelligence-based approaches have proven to be significantly effective in every branch of our daily lives, including healthcare and medical domains. During the early days of this pandemic, artificial intelligence (AI) was utilized in the fight against this virus outbreak and it has played a major role in containing the spread of the virus. It provided innovative opportunities to speed up the development of disease interventions. Several methods, models, AI-based devices, robotics, and technologies have been proposed and utilized for diverse tasks such as surveillance, spread prediction, peak time prediction, classification, hospitalization, healthcare management, heath system capacity, etc. This paper attempts to provide a quick, concise, and precise survey of the state-of-the-art AI-based techniques, technologies, and datasets used in fighting COVID-19. Several domains, including forecasting, surveillance, dynamic times series forecasting, spread prediction, genomics, compute vision, peak time prediction, the classification of medical imaging—including CT and X-ray and how they can be processed—and biological data (genome and protein sequences) have been investigated. An overview of the open-access computational resources and platforms is given and their useful tools are pointed out. The paper presents the potential research areas in AI and will thus encourage researchers to contribute to fighting against the virus and aid global health by slowing down the spread of the virus. This will be a significant contribution to help minimize the high death rate across the globe.

Suggested Citation

  • Umar Albalawi & Mohammed Mustafa, 2022. "Current Artificial Intelligence (AI) Techniques, Challenges, and Approaches in Controlling and Fighting COVID-19: A Review," IJERPH, MDPI, vol. 19(10), pages 1-24, May.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:10:p:5901-:d:814295
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    References listed on IDEAS

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    1. Cleo Anastassopoulou & Lucia Russo & Athanasios Tsakris & Constantinos Siettos, 2020. "Data-based analysis, modelling and forecasting of the COVID-19 outbreak," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-21, March.
    2. Yufang Wang & Kuai Xu & Yun Kang & Haiyan Wang & Feng Wang & Adrian Avram, 2020. "Regional Influenza Prediction with Sampling Twitter Data and PDE Model," IJERPH, MDPI, vol. 17(3), pages 1-12, January.
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