Prediction of Covid-19 cases using Machine Learning
Sounak Datta, Arka Sarkar, Iman Saha, Subir Baidya, Dr. Dharmpal Singh, Dr. Sudipta Sahana
COVID-19 , SARS-CoV-2 , Machine Learning , Data Analysis , Data Preprocessing , Feature Engineering.
Nowadays everyone is being effected from covid-19, In a country with such a huge population like India it is not very easy to test every individual due to shortage of medical kit availiability and everyone doesn’t have sufficient amount of money and resource . In this paper an effort has been made to design a simple system of detecting Covid-19 based on the symptoms using machine learning. Traditional and ensembled machine learning classifiers have been used, Logistic regression and Decision Tree Classifier is one of them . Logistic Regression showed better results than other ML algorithms by having nearly 97% testing accuracy . A Website was designed by which the users can select the symptoms (Y/N) very easily and also get the result depending on their inputs within a second . The framework made by us can be used, to prioritize testing for covid-19 when testing resources are not sufficient.This system can be used for early detection of covid-19 cases so that the person doesn’t have to go thorugh sever symptoms like difficulty in breathing and does not spread the virus to others.
Article Details
Unique Paper ID: 151519

Publication Volume & Issue: Volume 8, Issue 1

Page(s): 258 - 263
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