Artificial intelligence and Machine Learning based Techniques in Analyzing the COVID-19 Gene Expression data: A Review

Authors

Santhosh K, Department of Computer Science, JSS College for Women, Mysore, India
Ajitha S, Department of Master of Computer Applications, Ramaiah Institute of Technology, Bangalore
Sushma Pradeep, Department of Biotechnology and Bioinformatics, JSS Academy of Higher Education, Mysore, India
Kuralyanapalya Putta Honnappa Suresh, ICAR National Institute of Veterinary Epidemiology and Disease Informatics (NIVEDI), Bengaluru560064, Yelahanka, India
Sharanagouda S Patil, ICAR National Institute of Veterinary Epidemiology and Disease Informatics (NIVEDI), Bengaluru560064, Yelahanka, India
Shiva Prasad Kollur, Department of Sciences, AmritaSchool of Arts and Sciences, Amrita Vishwa Vidyapeetham, Mysuru Campus, Mysuru, India
Chandan Shivmallu, Department of Biotechnology and Bioinformatics, JSS Academy of Higher Education, Mysore, IndiaFollow

Abstract

The novel Coronavirus associated with respiratory illness has become a new threat to human health as it is spreading very rapidly among the human population. Scientists and healthcare specialists throughout the world are still looking for a breakthrough technology to help combat the Covid-19 outbreak, despite the recent worldwide urgency. The use of Machine Learning (ML) and Artificial Intelligence (AI) in earlier epidemics has encouraged researchers by providing a fresh approach to combating the latest Coronavirus pandemic. This paper aims to comprehensively review the role of AI and ML for analysis of gene expressed data of COVID-19

Recommended Citation

K, Santhosh; S, Ajitha; Pradeep, Sushma; Honnappa Suresh, Kuralyanapalya Putta; Patil, Sharanagouda S; Kollur, Shiva Prasad; and Shivmallu, Chandan (2022) "Artificial intelligence and Machine Learning based Techniques in Analyzing the COVID-19 Gene Expression data: A Review," International Journal of Health and Allied Sciences: Vol. 11: Iss. 1, Article 12.
DOI: 10.55691/2278-344X.1013
Available at: https://rescon.jssuni.edu.in/ijhas/vol11/iss1/12