Ecology, Environment and Conservation Paper

Vol. 28, oct Suppl. Issue 2022; Page No.(S405-S410)

ANALYSIS OF CONVOLUTION NEURAL NETWORK ALGORITHMS FORCLASSIFICATION OF COVID-19 COMPUTED TOMOGRAPHYIMAGES

Roopa V., Emilin Shyni and A. Christy Jeba Malar

Abstract

The very first infected novel coronavirus case (COVID-19) was found in Hubei, China in Dec.2019. TheCOVID-19 pandemic has spread over 214 countries and areas in the world, and has significantly affectedevery aspect of our daily lives. At the time of writing this article, the numbers of infected cases and deathsstill increase significantly and have no sign of a well-controlled situation, e.g., as of 13 July 2020, from atotal number of around 13.1 million positive cases, 571, 527 deaths were reported in the world.Motivatedby recent advances and applications of artificial intelligence (AI) and big data in various areas, this paperaims at emphasizing their importance in responding to the COVID-19 outbreak and preventingthe severeeffects of the COVID-19 pandemic. We firstly present an overview of AI and bigdata and then identify theapplications aimed at fighting against COVID-19, next highlight challenges and issuesassociated withstate-of-the-art solutions, and finally come up with recommendations for the communications to effectivelycontrol the COVID-19 situation. It is expected that this paper provides researchers and communities withnew insights into the ways AI and big data improve the COVID-19 situation, and drives further studies instopping the COVID-19 outbreak.