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@article{151519,
        author = {Sounak Datta and Arka Sarkar and Iman Saha and Subir Baidya and Dr. Dharmpal Singh and Dr. Sudipta Sahana},
        title = {Prediction of Covid-19 cases using Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {1},
        pages = {258-263},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=151519},
        abstract = {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.},
        keywords = {COVID-19 , SARS-CoV-2 , Machine Learning , Data Analysis , Data Preprocessing , Feature Engineering.},
        month = {},
        }