Swati Jayade, D. Ingole, M. D. Ingole, Aditya Tohare
{"title":"Cholera Disease Detection using Fuzzy Logic Technique","authors":"Swati Jayade, D. Ingole, M. D. Ingole, Aditya Tohare","doi":"10.1109/ICECIE52348.2021.9664703","DOIUrl":null,"url":null,"abstract":"In this research paper, a fuzzy based system is presented for the diagnosis of cholera disease. It provides decision support platform to the scientists, researchers, physicians and healthcare practitioners in cholera disease area. The given fuzzy expert system contains major components as; the Fuzzification, Knowledge base, Inference engine and Defuzzification module. This system is implemented based on observations of patients, medical diagnosis and the expert’s knowledge. The system is developed based on Mamdani's fuzzy inference system. It does the reasoning and inference the data from the rules designed. In this method in order to get the decision results majorly the symptoms considered are like mild, moderate and severe. To do the experimental analysis and study thirty patients of cholera disease are selected and considered. The outcomes are calculated and checked with domain knowledge experts. This system will be helpful for making the cholera diagnosis as the medical practitioners can directly input the symptoms and will get the results to take the decision.","PeriodicalId":309754,"journal":{"name":"2021 3rd International Conference on Electrical, Control and Instrumentation Engineering (ICECIE)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 3rd International Conference on Electrical, Control and Instrumentation Engineering (ICECIE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECIE52348.2021.9664703","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In this research paper, a fuzzy based system is presented for the diagnosis of cholera disease. It provides decision support platform to the scientists, researchers, physicians and healthcare practitioners in cholera disease area. The given fuzzy expert system contains major components as; the Fuzzification, Knowledge base, Inference engine and Defuzzification module. This system is implemented based on observations of patients, medical diagnosis and the expert’s knowledge. The system is developed based on Mamdani's fuzzy inference system. It does the reasoning and inference the data from the rules designed. In this method in order to get the decision results majorly the symptoms considered are like mild, moderate and severe. To do the experimental analysis and study thirty patients of cholera disease are selected and considered. The outcomes are calculated and checked with domain knowledge experts. This system will be helpful for making the cholera diagnosis as the medical practitioners can directly input the symptoms and will get the results to take the decision.