Sujadi, I, Natalia, F, Ferdinand, FV, Sudirman, S and Ko, CS (2022) A Mobile-Based COVID-19 Decision Support System Using Dempster-Shafer Theory. ICIC Express Letters, Part B: Applications, 13 (6). pp. 615-622. ISSN 2185-2766

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Abstract

COVID-19 testing hesitancy is problematic but prevalent in many developing countries. Because of this, many governments face difficulties in limiting the rate of spread of the disease since it will impact adversely on the effectiveness of the track-and-trace program. This problem is a result of the relatively high cost of the test in these countries compared to the income of the population which has put off many people in getting the test. While the majority of the population recognize the importance of getting the test, many do not want to spend their money because they are unsure if they should, based on the symptoms they are experiencing. Also, ideally, people should be able to consult their General Practitioners to discuss their symptoms but to many people in developing countries, this may also be unaffordable. In this paper, we detail our solution that can improve this situation by developing a COVID-19 decision support system that is deployed as a mobile application. This application allows its user to enter the type of symptoms they are experiencing and provide a recommendation on whether to seek further medical advice or not. The application uses the Dempster-Shafer Theory and statistical inference based on the knowledge database developed through opinions gathered from medical experts. The process considers the similarity of symptoms of COVID-19 disease with several other diseases. The mobile application has also several features that are designed to help increase the understanding and awareness of its users about the disease and educate them about how to maintain their health and safety during the pan-demic.

Item Type:	Article
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Divisions:	Computer Science & Mathematics
Publisher:	ICIC International
SWORD Depositor:	A Symplectic
Date Deposited:	06 Mar 2023 12:47
Last Modified:	06 Mar 2023 13:00
DOI or ID number:	10.24507/icicelb.13.06.615
URI:	https://researchonline.ljmu.ac.uk/id/eprint/18994

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