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. 2020 Jul 8:8:128776-128795.
doi: 10.1109/ACCESS.2020.3007939. eCollection 2020.

AI Techniques for COVID-19

Adedoyin Ahmed Hussain  1   2 , Ouns Bouachir  3   4 , Fadi Al-Turjman  2 , Moayad Aloqaily  5
Affiliations

AI Techniques for COVID-19

Adedoyin Ahmed Hussain et al. IEEE Access. .

Abstract

Artificial Intelligence (AI) intent is to facilitate human limits. It is getting a standpoint on human administrations, filled by the growing availability of restorative clinical data and quick progression of insightful strategies. Motivated by the need to highlight the need for employing AI in battling the COVID-19 Crisis, this survey summarizes the current state of AI applications in clinical administrations while battling COVID-19. Furthermore, we highlight the application of Big Data while understanding this virus. We also overview various intelligence techniques and methods that can be applied to various types of medical information-based pandemic. We classify the existing AI techniques in clinical data analysis, including neural systems, classical SVM, and edge significant learning. Also, an emphasis has been made on regions that utilize AI-oriented cloud computing in combating various similar viruses to COVID-19. This survey study is an attempt to benefit medical practitioners and medical researchers in overpowering their faced difficulties while handling COVID-19 big data. The investigated techniques put forth advances in medical data analysis with an exactness of up to 90%. We further end up with a detailed discussion about how AI implementation can be a huge advantage in combating various similar viruses.

Keywords: Big data; artificial intelligence; cloud computing; deep learning; the IoT.

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Figures

FIGURE 1.
FIGURE 1.
Data types considered in AI concerning COVID-19.
FIGURE 2.
FIGURE 2.
Supervised learning technique approach.
FIGURE 3.
FIGURE 3.
Illustration of the unsupervised learning technique.
FIGURE 4.
FIGURE 4.
Illustration of the reinforcement learning technique.
FIGURE 5.
FIGURE 5.
SVM illustration.
FIGURE 6.
FIGURE 6.
Neural network illustration.
See this image and copyright information in PMC

References

    1. Murdoch T. B. and Detsky A. S., “The inevitable application of big data to health care,” J. Amer. Med. Assoc. vol. 309, no. , pp. 1351–1352, 2013. - PubMed
    1. Kolker E., Özdemir V., and Kolker E., “How healthcare can refocus on its super-customers (patients, n = 1) and customers (doctors and nurses) by leveraging lessons from Amazon, Uber, and Watson,” OMICS, J. Integrative Biol., vol. 20, no. 6, pp. 33–329, 2016. - PubMed
    1. Dilsizian S. E. and Siegel E. L., “Artificial intelligence in medicine and cardiac imaging: Harnessing big data and advanced computing to provide personalized medical diagnosis and treatment,” Current Cardiol. Rep., vol. 16, no. 1, p. 441, Jan. 2014. - PubMed
    1. Xu X., Chen P., Wang J., Feng J., Zhou H., Li X., Zhong W., and Hao P., “Evolution of the novel coronavirus from the ongoing Wuhan outbreak and modeling of its spike protein for risk of human transmission,” Sci. China Life Sci., vol. 63, no. 3, pp. 457–460, Mar. 2020, doi: 10.1007/s11427-020-1637-5. - DOI - PMC - PubMed
    1. Huang C.et al., “Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China,” Lancet, vol. 395, pp. 497–506, Feb. 2020, doi: 10.1016/S0140-6736(20)30183-5. - DOI - PMC - PubMed

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