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A novel diagnosis system for detection of kidney disease by a fuzzy soft decision-making problem.

Authors :
Khalil, Ahmed Mostafa
Zahran, Ahmed Mohamed
Basheer, Rehab
Source :
Mathematics & Computers in Simulation. Jan2023, Vol. 203, p271-305. 35p.
Publication Year :
2023

Abstract

According to the 2017 World Health Organization (WHO) report, a large part of Egypt suffers from kidney disease. In recent years, kidney disease has become a leading cause of death worldwide, according to the report provided by the National Kidney Research Foundation. In the present paper, we will propose a novel method to predict kidney disease depending on the seven symptoms (i.e., Nephron Functionality, Blood Sugar, Systolic and Diastolic Blood Pressure, Alcohol Intake, Weight, and Age). Further, we design the new expert system (i.e., a fuzzy soft expert system) based on five basic steps to help the researcher and specialist doctor to predict kidney disease. After an exploratory study, which took it from the 60 patients (i.e., thirty males and thirty females) showed symptoms similar to kidney disease they have been conducting this study through (Nephrology Department, Damanhour Teaching Hospital, Beheira Governorate, Egypt). Accordingly, the user system provides helpful and reliable diagnostic results to predict kidney disease or kidney failure. Lastly, we present the comparison between the soft fuzzy expert system and Shakil et al.'s fuzzy expert system. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03784754
Volume :
203
Database :
Academic Search Index
Journal :
Mathematics & Computers in Simulation
Publication Type :
Periodical
Accession number :
159268769
Full Text :
https://doi.org/10.1016/j.matcom.2022.06.014