Paper Info
Title
Fusion of AI techniques to tackle COVID-19 pandemic: models, incidence rates, and future trends
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.
Year
DOI
Venue
2022
10.1007/s00530-021-00818-1
Multimedia Systems
Keywords
DocType
Volume
AI, COVID-19, Healthcare, Machine learning, Deep learning
Journal
28
Issue
ISSN
Citations 
4
0942-4962
0
PageRank 
References 
Authors
0.34
24
5
Name
Order
Citations
PageRank
Het Shah131.72
Saiyam Shah200.34
Sudeep Tanwar32410.35
Rajesh Gupta425.46
Neeraj Kumar52889236.13