Please use this identifier to cite or link to this item:
https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/2527
Title: | A Novel Approach For Predicting Covid-19 Using Machine Learning-Based Logistic Regression Classification Model |
Authors: | Ravi, Jayavadivel |
Keywords: | COVID-19 Machine learning|Ppandemic IT services industry Coronavirus DiseaseS |
Issue Date: | 2023 |
Publisher: | IGI Global |
Citation: | Chapter 2; pp. 18-30 |
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. © 2023, IGI Global. All rights reserved. |
URI: | https://doi.org/10.4018/978-1-6684-8306-0.ch002 http://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/2527 |
ISBN: | 9781668483084 9781668483060 |
Appears in Collections: | Book/ Book Chapters |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.