Fuzzy Cloud Based COVID-19 Diagnosis Assistant for identifying affected cases globally using MCDM

Shahnawaz Ahmad; Shabana Mehfuz; Javed Beg; Nadeem Ahmad Khan; Afzal Husain Khan

doi:10.1016/j.matpr.2021.01.240

Fuzzy Cloud Based COVID-19 Diagnosis Assistant for identifying affected cases globally using MCDM

Mater Today Proc. 2021 Jan 29. doi: 10.1016/j.matpr.2021.01.240. Online ahead of print.

Authors

Shahnawaz Ahmad¹, Shabana Mehfuz², Javed Beg³, Nadeem Ahmad Khan⁴, Afzal Husain Khan⁴

Affiliations

¹ Department of Electrical Engineering, Jamia Millia Islamia (A Central University), New Delhi-110025, India.
² Oracle, India.
³ Civil Engineering Department, Jamia Millia Islamia (A Central University), New Delhi-110025, India.
⁴ Civil Engineering Department, Jazan University, 114 Jazan, Saudi Arabia.

Abstract

The COVID-19, Coronavirus Disease 2019, emerged as a hazardous disease that led to many causalities across the world. Early detection of COVID-19 in patients and proper treatment along with awareness can help to contain COVID-19. Proposed Fuzzy Cloud-Based (FCB) COVID-19 Diagnosis Assistant aims to identify the patients as confirmed, suspects, or suspicious of COVID-19. It categorized the patients into four categories as mild, moderate, severe, or critical. As patients register themselves online on the FCB COVID-19 DA in real-time, it creates the database for the same. This database helps to improve diagnostic accuracy as it contains the latest updates from real-world cases data. A team of doctors, experts, consultants are integrated with the FCB COVID-19 DA for better consultation and prevention. The ultimate aim of this proposed theory of FCB COVID-19 DA is to take control of COVID-19 pandemic and de-accelerate its rate of transmission among the society.

Keywords: COVID-19; MCDM; cloud computing; diagnosis assistant; fuzzy set theory.