Monitoring and Controlling System of COVID-19 Symptoms Using Random Forest

Authors

  • Vivek Bhardwaj Assistant Professor, Department of Computer Application, Government Maharani Laxmi Bai Girls Post Graduate Autonomous College, Bhopal, Madhya Pradesh, India
  • Sharad Pathak Assistant Professor, Department of Statistics, Government Maharani Laxmi Bai Girls Post Graduate Autonomous College, Bhopal, Madhya Pradesh, India

Keywords:

COVID-19, Machine Learning, Cloud Computing, Classification.

Abstract

Corona virus (COVID-19) has already claimed hundreds of lives and infected millions of people around the world. The early detection of COVID-19 is shown in this paper. Machine learning random forest techniques were used to implement the detection procedure on cloud computing. Objectives of the study is to provide health assurance directly from home using some smart tools with cloud computing. Our research contribute the categorization of patients into different categories, continuous monitoring of infected patients and identifying the probabilities of each user in spreading or receiving the infection by analyze users relationship with infected patients. 10-fold cross-validations were implemented during the classification process. Accuracy, precision, recalls, F-Measure, MCC were used to evaluate the classification process. The correctly classified instance was obtained as 99.95%. 

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Published

2022-06-18

Issue

Vol. 11 No. 1 (2022)

Section

Review Article

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