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Review Article Open Access

Artificial Intelligence in COVID-19 Management: A Systematic Review

Samaneh Mohammadi1,2, SeyedAhmad SeyedAlinaghi2, Mohammad Heydari3, Zahra Pashaei2,4, Pegah Mirzapour2, Amirali Karimi5, Amir Masoud Afsahi6, Peyman Mirghaderi7, Parsa Mohammadi5, Ghazal Arjmand8, Yasna Soleimani9, Ayein Azarnoush10, Hengameh Mojdeganlou11, Mohsen Dashti12, Hadiseh Azadi Cheshmekabodi13, Sanaz Varshochi5, Mohammad Mehrtak14, Ahmadreza Shamsabadi15, Esmaeil Mehraeen3 and Daniel Hackett16
  • 1 Department of Health Information Technology, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
  • 2 Iranian Research Center for HIV/AIDS, Iranian Institute for Reduction of High-Risk Behaviors, Tehran University of Medical Sciences, Tehran, Iran
  • 3 Department of Health Information Technology, Khalkhal University of Medical Sciences, Khalkhal, Iran
  • 4 Department of Nursing, University of British Columbia, Vancouver, Canada
  • 5 Department of Medicine, Tehran University of Medical Sciences, Tehran, Iran
  • 6 Department of Radiology, School of Medicine, University of California, San Diego (UCSD), California, United States
  • 7 Students' Scientific Research Center (SSRC), Tehran University of Medical Sciences, Tehran, Iran
  • 8 Department of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
  • 9 Department of Medicine, Islamic Azad University, Tehran, Iran
  • 10 Department of Medicine, Alborz University of Medical Sciences, Karaj, Alborz, Iran
  • 11 Department of Pathology, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
  • 12 Department of Radiology, Tabriz University of Medical Sciences, Tabriz, Iran
  • 13 Department of Health Information Technology, School of Health Information Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran
  • 14 Department of Healthcare Services Management, School of Medicine and Allied Medical Sciences, Ardabil University of Medical Sciences, Ardabil, Iran
  • 15 Department of Health Information Technology, Esfarayen Faculty of Medical Sciences, Esfarayen, Iran
  • 16 Department of Physical Activity, School of Health Sciences, Lifestyle, Ageing, and Wellbeing Faculty Research Group, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia

Abstract

With the development of modern technologies in the field of healthcare, the use of Artificial Intelligence (AI) in disease management is increasing. AI methods may assist healthcare providers in the COVID-19 era. The current study aimed to observe the efficacy and importance of AI for managing the COVID-19 pandemic. An organized search was conducted, utilizing PubMed, Web of Science, Scopus, Embase, and Cochrane up to September 2022. Studies were considered qualified for inclusion if they met the inclusion criterion. We conducted review according to the Preferred Reporting Items for Systematic reviews and Meta Analyses (PRISMA) guidelines. There were 52 documents that met the eligibility criteria to be included in the review. The most common item using AI during the COVID-19 era was predictive models to foretell pneumonia and mortality risks in people with COVID-19 based on medical and experimental parameters. COVID-19 mortality was related to being male and elderly based on the Artificial Neural Network (ANN) and Convolutional Neural Network (CNN) logistic regression analysis of demographics, clinical data, and laboratory tests of hospitalized COVID-19 patients. AI can predict, diagnose and model COVID-19 by using techniques such as support vector machines, decision trees, and neural networks. It is suggested that future research should deal with the design and development of AI-based tools for the management of chronic diseases such as COVID-19.

Journal of Computer Science
Volume 19 No. 5, 2023, 554-568

DOI: https://doi.org/10.3844/jcssp.2023.554.568

Submitted On: 4 November 2022 Published On: 30 March 2023

How to Cite: Mohammadi, S., SeyedAlinaghi, S., Heydari, M., Pashaei, Z., Mirzapour, P., Karimi, A., Afsahi, A. M., Mirghaderi, P., Mohammadi, P., Arjmand, G., Soleimani, Y., Azarnoush, A., Mojdeganlou, H., Dashti, M., Cheshmekabodi, H. A., Varshochi, S., Mehrtak, M., Shamsabadi, A., Mehraeen, E. & Hackett, D. (2023). Artificial Intelligence in COVID-19 Management: A Systematic Review. Journal of Computer Science, 19(5), 554-568. https://doi.org/10.3844/jcssp.2023.554.568

Open AccessCopyright: © 2023 Samaneh Mohammadi, SeyedAhmad SeyedAlinaghi, Mohammad Heydari, Zahra Pashaei, Pegah Mirzapour, Amirali Karimi, Amir Masoud Afsahi, Peyman Mirghaderi, Parsa Mohammadi, Ghazal Arjmand, Yasna Soleimani, Ayein Azarnoush, Hengameh Mojdeganlou, Mohsen Dashti, Hadiseh Azadi Cheshmekabodi, Sanaz Varshochi, Mohammad Mehrtak, Ahmadreza Shamsabadi, Esmaeil Mehraeen and Daniel Hackett. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Keywords

  • COVID-19
  • SARS-CoV-2
  • Artificial Intelligence (AI)
  • Deep Learning
  • Machine Learning
  • Predicting