A Novel Approach for Predicting COVID-19 Using Machine Learning-Based Logistic Regression Classification MODEL

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Author(s): Jayavadivel Ravi (Department of Computer Science and Engineering, Alliance University, Bangalore, India)
Copyright: 2023
Pages: 13
Source title: Perspectives on Social Welfare Applications’ Optimization and Enhanced Computer Applications
Source Author(s)/Editor(s): Ponnusamy Sivaram (G.H. Raisoni College of Engineering, Nagpur, India), S. Senthilkumar (University College of Engineering, BIT Campus, Anna University, Tiruchirappalli, India), Lipika Gupta (Department of Electronics and Communication Engineering, Chitkara University Institute of Engineering and Technology, Chitkara University, India)and Nelligere S. Lokesh (Department of CSE-AIML, AMC Engineering College, Bengaluru, India)
DOI: 10.4018/978-1-6684-8306-0.ch002

Keywords: Engineering Science Reference / Human Aspects of Technology / Social Sciences & Humanities / Systems and Software Engineering

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Abstract

Recently, several studies have stated that mild weather can perhaps halt the global epidemic, which has already afflicted over 1.6 million people globally. Clarification of such correlations in the worst affected country, the US, can be extremely valuable to understand the function of weather in transmission of the disease in the highly populated countries, such as India. The authors developed a machine-learning approach as logistic regression classification models that used data from several sources to determine whether a patient is at risk of COVID-19 using one of the classification models with the greatest accuracy. They are working on a model that uses simple features available through basic clinical inquiries to detect COVID-19 patients. When testing resources are tight, their approach can be used to prioritize testing for COVID-19, among other things.

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A Novel Approach for Predicting COVID-19 Using Machine Learning-Based Logistic Regression Classification MODEL

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