COVID-19 IDENTIFIER USING SMLT AND DATA SCIENCE

COVID-19 IDENTIFIER USING SMLT AND DATA SCIENCE

Mr. A. SATHEESH, AJITH S, PRANESH S, RICHARD JOSEPH P P, SURYA K

DEPT OF COMPUTER SCIENE AND ENGINEERING

JEPPIAAR INSTITUTE OF TECHNOLOGY

Abstract- The worldwide population has been devastated by the Coronavirus Disease 2019 (COVID-19) pandemic, which began in Wuhan, China, and has overloaded advanced healthcare systems around the world. WHO is actively monitoring and responding to this epidemic. The current rapid and exponential increase in the number of patients has prompted the use of AI approaches to forecast the likely result of an infected patient in order to provide suitable therapy. The goal is to determine whether machine learning-based algorithms can accurately anticipate whether or not covid-19 recovery is achievable. The supervised machine learning approach (SMLT) is used to evaluate the dataset and capture various information such as variable identification, uni-variate analysis, bi-variate and multi-variate analysis, missing value treatments, and data validation, data cleaning/preparing, and data analysis.

Keywords: Covid-19 and Deep Learning, Machine Learning Algorithms, Supervised Machine Learning Techniques (SMLT)