Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2021;11(6):1311-1320.
doi: 10.1007/s12553-021-00601-2. Epub 2021 Sep 28.

The prospective of Artificial Intelligence in COVID-19 Pandemic

Swati Swayamsiddha  1 , Kumar Prashant  2 , Devansh Shaw  2 , Chandana Mohanty  3
Affiliations
Review

The prospective of Artificial Intelligence in COVID-19 Pandemic

Swati Swayamsiddha et al. Health Technol (Berl). 2021.

Abstract

Coronavirus disease 2019 (COVID-19) is a major threat throughout the world. The latest advancements in the field of computational techniques based on Artificial Intelligence (AI), Machine Learning (ML) and Big Data can help in detecting, monitoring and forecasting the severity of the COVID-19 pandemic. We aim to review the detection of the COVID-19 pandemic empowered by AI, major implications, challenges and the future of smart health care at a glance. The AI plays a pioneering role in rapid and improved detection of the disease. It helps in modeling the disease activity and predicting the severity for better decision making and preparedness by healthcare authorities and policymakers. It is a promising technology for automatic and fully transparent monitoring system to track and treat the patients remotely without spreading the virus to others. The future application areas of AI-based healthcare are also identified. The role of AI in tackling the COVID-19 pandemic is reviewed in this paper. AI proves beneficial in early detection with improved results. It also provides solution for contact tracing, prediction, drug development thus reducing the workload of medical industry.

Keywords: Artificial Intelligence; COVID-19; Coronavirus; SARS-CoV-2.

PubMed Disclaimer

Conflict of interest statement

Informed consentThe authors confirm that this article content has no conflict of interest. I further confirm that this article is original and has not been published elsewhere nor is it currently under consideration for publication elsewhereConflict of interest ◦ All authors have participated in (a) conception and design, or analysis and interpretation of the data; (b) drafting the article or revising it critically for important intellectual content; and (c) approval of the final version. ◦ This manuscript has not been submitted to, nor is under review at, another journal or other publishing venue. ◦ The authors have no affiliation with any organization with a direct or indirect financial interest in the subject matter discussed in the manuscript ◦ The following authors have affiliations with organizations with direct or indirect financial interest in the subject matter discussed in the manuscript:

Figures

Fig. 1
Fig. 1
Schematic figure of the SARS-CoV-2. The SP, MP, and NP are the viral surface proteins that are embedded in a lipid bilayer envelope (EP). The genome is a single-stranded positive-sense viral RNA that is associated with the nucleocapsid protein (NP)
Fig. 2
Fig. 2
Schematic diagram showing the replicating cycle of SARS-CoVs-2
Fig. 3
Fig. 3
Schematic diagram showing the conventional general procedure and AI-based applications that generally followed by clinicians to detect the COVID-19 patients
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

References

    1. Haleem A, Javaid M, Vaishya R. Effects of COVID-19 pandemic in daily life. Curr Med Res Pract. 2020;10(2):78–79. doi: 10.1016/j.cmrp.2020.03.011. - DOI - PMC - PubMed
    1. Ting DSW, Carin L, Dzau V, Wong TY. Digital technology and COVID-19. Nat Med. 2020;26(4):459–461. doi: 10.1038/s41591-020-0824-5. - DOI - PMC - PubMed
    1. World meter hwwic. 2020 May 8.
    1. Di Wu, Tiantian Wu, Liu Q. The SARS-CoV-2 outbreak: What we know. Int J Infect Dis 2020;94(2):44–8. - PMC - PubMed
    1. Swayamsiddha S, Mohanty C. Application of cognitive Internet of Medical Things for COVID-19 pandemic. Diabetes Metab Syndr. 2020;14(5):911–915. doi: 10.1016/j.dsx.2020.06.014. - DOI - PMC - PubMed

LinkOut - more resources