Year : 2020, Volume : 10, Issue : 2
First page : ( 55) Last page : ( 62)
Print ISSN : 2249-3212. Online ISSN : 2249-3220. Published online : 2020 November 14.
Article DOI : 10.5958/2249-3220.2020.00008.7

Data Mining Applications for Predicting the COVID-19 Pattern

Jatain Aman^1,*, Assistant Professor

¹Department of Computer science, Amity University, Haryana, India

*e-mail: amanjatainsingh@gmail.com

Received:  9  December,  2020; Accepted:  21  May,  2021.

Abstract

The knowledge discovery in databases (KDD) is alarmed by the development of methods and techniques for the use of data. Data mining is one of the most critical phases of the KDD. Data mining is a method of pattern discovery and extraction where there is a large amount of data involved. Electronic health records are becoming increasingly common in health care organisations. With increased access to a substantial amount of patient data, healthcare companies are now in a position to optimise the efficiency and quality of their businesses through data mining. COVID-19 is a new global epidemic in 186 countries around the world. And as a result of this pandemic, patient data are being introduced at a quicker rate. Search engines have valuable data from populations and these data can be useful for the study of epidemics. Using data mining tools for available data will provide deeper insight into the management of the coronavirus outbreak health problem for each country and the world. In order to contribute to the well-being of the living population, the research will analyse coronavirus actions in the previous months and will display statistics using different models, data mining techniques. Various data mining models and methods will demonstrate the pattern of the COVID-19 over the year.

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Keywords:

COVID-19, KDD, Data mining, Health, Pattern.

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