Predicting the Possibility of COVID-19 Infection Using Fuzzy Logic System

Posted on:May 3, 2021 at 12:00 AM

image

Full Paper

Abstract

Diagnosing COVID-19 in a fast and efficient manner is an ongoing problem. Currently, the methods of detection involve physical tests. Physical tests have the disadvantage that they require either test kits or medical equipment. This paper outlines the design of a type-2 fuzzy logic system that can help provide a preliminary diagnosis by computing the possibility that a patient is suffering from COVID-19 based on their external symptoms. It uses input information that can be gleaned without need for medical procedures. Both statistical data and the knowledge base were garnered from publicly available databases and datasets. The fuzzy logic system implemented here is functional, but it is fairly inaccurate and illustrates that more information, both symptomatic and epidemiological is needed, to predict COVID-19 infections through an expert system.

Code

Available on Github

Credits

Shadab Hafiz Choudhury 1, Azmary Jannat Aurin 1, Tanbin Akter Mitaly 1 and Dr. Mohammed Rashedur Rahman 1 2

1: Department of Electrical and Computer Engineering, North South University
2: Corresponding Author

Citation

@article{choudhury_predicting_2021,
	title = {Predicting the possibility of {COVID}-19 infection using fuzzy logic system},
	volume = {14},
	issn = {1751-5858},
	url = {https://www.inderscienceonline.com/doi/abs/10.1504/IJIIDS.2021.116465},
	doi = {10.1504/IJIIDS.2021.116465},
	number = {3},
	urldate = {2024-03-16},
	journal = {International Journal of Intelligent Information and Database Systems},
	author = {Choudhury, Shadab Hafiz and Aurin, Azmary Jannat and Mitaly, Tanbin Akter and Rahman, Rashedur M.},
	month = jan,
	year = {2021},
	note = {Publisher: Inderscience Publishers},
	keywords = {COVID-19, iterative type-2 fuzzy logic system, Mamdani fuzzy inference, novel coronavirus},
	pages = {239--256},
}