Software-Based Testing Kit Using Machine Learning for Diagnosis and Predictive Analytics of COVID-19 Patients

Vishal Kumar Goar and Jyoti Prabha
Additional contact information
Vishal Kumar Goar: Government Engineering College, Bikaner, India
Jyoti Prabha: University College of Engineering and Technology, Bikaner, India

International Journal of Information System Modeling and Design (IJISMD), 2021, vol. 12, issue 2, 39-50

Abstract: Nowadays, the global community is being affected with COVID-19 disease and integrated infections, which are becoming a menace to the whole world. Research is going on to find out the solution, and still, no particular vaccination or solution has been achieved. This research work is focusing on the analytics of dataset extracted, which has assorted attributes, and these attributes are processed in the machine learning algorithm so that the prime factor can be recognized. In this research manuscript, the usage of COVID-19 dataset is done and trained using supervised learning approach of artificial neural network (ANN) on Levenberg-Marquardt (LM) algorithm so that the predictions of the test patients can be done on the key attributes of age, gender, location, and related parameters. The selection of LM-based implementation with ANN is done as it is the faster approach compared to other functions in neural networks.

Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
https://services.igi-global.com/resolvedoi/resolve ... 18/IJISMD.2021040103 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jismd0:v:12:y:2021:i:2:p:39-50

Access Statistics for this article

International Journal of Information System Modeling and Design (IJISMD) is currently edited by Thierry O. C. Edoh

More articles in International Journal of Information System Modeling and Design (IJISMD) from IGI Global
Bibliographic data for series maintained by Journal Editor ().