Fusion of AI techniques to tackle COVID-19 pandemic: models, incidence rates, and future trends

Het Shah; Saiyam Shah; Sudeep Tanwar; Rajesh Gupta; Neeraj Kumar

doi:10.1007/s00530-021-00818-1

Fusion of AI techniques to tackle COVID-19 pandemic: models, incidence rates, and future trends

Multimed Syst. 2022;28(4):1189-1222. doi: 10.1007/s00530-021-00818-1. Epub 2021 Jul 13.

Authors

Het Shah¹, Saiyam Shah¹, Sudeep Tanwar¹, Rajesh Gupta¹, Neeraj Kumar^{2

3

4}

Affiliations

¹ Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad, India.
² Department of Computer Science Engineering, Thapar Institute of Engineering and Technology, Deemed to be University, Patiala, India.
³ School of Computer Science, University of Petroleum and Energy Studies, Dehradun, Uttarakhand India.
⁴ King Abdul Aziz University, Jeddah, Saudi Arabia.

Abstract

The COVID-19 pandemic is rapidly spreading across the globe and infected millions of people that take hundreds of thousands of lives. Over the years, the role of Artificial intelligence (AI) has been on the rise as its algorithms are getting more and more accurate and it is thought that its role in strengthening the existing healthcare system will be the most profound. Moreover, the pandemic brought an opportunity to showcase AI and healthcare integration potentials as the current infrastructure worldwide is overwhelmed and crumbling. Due to AI's flexibility and adaptability, it can be used as a tool to tackle COVID-19. Motivated by these facts, in this paper, we surveyed how the AI techniques can handle the COVID-19 pandemic situation and present the merits and demerits of these techniques. This paper presents a comprehensive end-to-end review of all the AI-techniques that can be used to tackle all areas of the pandemic. Further, we systematically discuss the issues of the COVID-19, and based on the literature review, we suggest their potential countermeasures using AI techniques. In the end, we analyze various open research issues and challenges associated with integrating the AI techniques in the COVID-19.

Keywords: AI; COVID-19; Deep learning; Healthcare; Machine learning.