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

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.(c) 2022 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.