{"title":"皮肤病诊断的模糊专家系统设计","authors":"Muhammad Asim Ali Raza, M. Liaqat, M. Shoaib","doi":"10.23919/ICACS.2019.8689140","DOIUrl":null,"url":null,"abstract":"Skin diseases are common in rural communities and flood affected areas. Preferably, skin disease should be treated without delay by a dermatologist. But due to shortage of expertise in rural areas, it is impossible so far. An expert system is capable of providing timely and correct diagnosis, that’s why building an expert system is a potential challenge. In this paper we will present a design of fuzzy expert system for the detection of skin (erythemato squamous) diseases. Because uncertainty and impreciseness among the symptoms in diagnosis process, we choose fuzzy logic based design. Fuzzy logic facilitates to deal with imprecise boundaries of input symptoms in medical expert system. Consequently, reliability of systems results will increase. For implementing the system, we use MATLAB fuzzy logic toolbox. Fuzzy logic controller generates a result from given symptoms using Mamdani MIN-MAX inference mechanism and for defuzzification uses centroid (COG) method. The accuracy of the designed fuzzy expert system was 90.27%. Furthermore, fuzzy expert system effectively used in health care for detecting and healing of erythemato squamous diseases.","PeriodicalId":290819,"journal":{"name":"2019 2nd International Conference on Advancements in Computational Sciences (ICACS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A Fuzzy Expert System Design for Diagnosis of Skin Diseases\",\"authors\":\"Muhammad Asim Ali Raza, M. Liaqat, M. Shoaib\",\"doi\":\"10.23919/ICACS.2019.8689140\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Skin diseases are common in rural communities and flood affected areas. Preferably, skin disease should be treated without delay by a dermatologist. But due to shortage of expertise in rural areas, it is impossible so far. An expert system is capable of providing timely and correct diagnosis, that’s why building an expert system is a potential challenge. In this paper we will present a design of fuzzy expert system for the detection of skin (erythemato squamous) diseases. Because uncertainty and impreciseness among the symptoms in diagnosis process, we choose fuzzy logic based design. Fuzzy logic facilitates to deal with imprecise boundaries of input symptoms in medical expert system. Consequently, reliability of systems results will increase. For implementing the system, we use MATLAB fuzzy logic toolbox. Fuzzy logic controller generates a result from given symptoms using Mamdani MIN-MAX inference mechanism and for defuzzification uses centroid (COG) method. The accuracy of the designed fuzzy expert system was 90.27%. Furthermore, fuzzy expert system effectively used in health care for detecting and healing of erythemato squamous diseases.\",\"PeriodicalId\":290819,\"journal\":{\"name\":\"2019 2nd International Conference on Advancements in Computational Sciences (ICACS)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 2nd International Conference on Advancements in Computational Sciences (ICACS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/ICACS.2019.8689140\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 2nd International Conference on Advancements in Computational Sciences (ICACS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/ICACS.2019.8689140","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Fuzzy Expert System Design for Diagnosis of Skin Diseases
Skin diseases are common in rural communities and flood affected areas. Preferably, skin disease should be treated without delay by a dermatologist. But due to shortage of expertise in rural areas, it is impossible so far. An expert system is capable of providing timely and correct diagnosis, that’s why building an expert system is a potential challenge. In this paper we will present a design of fuzzy expert system for the detection of skin (erythemato squamous) diseases. Because uncertainty and impreciseness among the symptoms in diagnosis process, we choose fuzzy logic based design. Fuzzy logic facilitates to deal with imprecise boundaries of input symptoms in medical expert system. Consequently, reliability of systems results will increase. For implementing the system, we use MATLAB fuzzy logic toolbox. Fuzzy logic controller generates a result from given symptoms using Mamdani MIN-MAX inference mechanism and for defuzzification uses centroid (COG) method. The accuracy of the designed fuzzy expert system was 90.27%. Furthermore, fuzzy expert system effectively used in health care for detecting and healing of erythemato squamous diseases.