{"title":"基于模糊逻辑对人体观察到的体征进行诊断分析的正常程度","authors":"Y. Hata, O. Ishikawa, Syoji Kobashi, K. Kondo","doi":"10.1109/NAFIPS.2003.1226773","DOIUrl":null,"url":null,"abstract":"This paper defines normality in human body for diagnostic analysis of signs observed in human body. The normality is a matter of degree. Physician usually examines whether a patient is either normal or abnormal. Diagnosis of human body is usually done by observing biosignals, radiological images, body surface information and others of human body. First, the information granularity of these signs of human body is shown. The normality is defined in the theory of hierarchical definability. According to the definition, a calculation method of the degree of normality is introduced. Finally, the examples of the degree of normality are shown.","PeriodicalId":153530,"journal":{"name":"22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Degree of normality based on fuzzy logic for a diagnostic analysis of signs observed in a human body\",\"authors\":\"Y. Hata, O. Ishikawa, Syoji Kobashi, K. Kondo\",\"doi\":\"10.1109/NAFIPS.2003.1226773\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper defines normality in human body for diagnostic analysis of signs observed in human body. The normality is a matter of degree. Physician usually examines whether a patient is either normal or abnormal. Diagnosis of human body is usually done by observing biosignals, radiological images, body surface information and others of human body. First, the information granularity of these signs of human body is shown. The normality is defined in the theory of hierarchical definability. According to the definition, a calculation method of the degree of normality is introduced. Finally, the examples of the degree of normality are shown.\",\"PeriodicalId\":153530,\"journal\":{\"name\":\"22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-07-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NAFIPS.2003.1226773\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NAFIPS.2003.1226773","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Degree of normality based on fuzzy logic for a diagnostic analysis of signs observed in a human body
This paper defines normality in human body for diagnostic analysis of signs observed in human body. The normality is a matter of degree. Physician usually examines whether a patient is either normal or abnormal. Diagnosis of human body is usually done by observing biosignals, radiological images, body surface information and others of human body. First, the information granularity of these signs of human body is shown. The normality is defined in the theory of hierarchical definability. According to the definition, a calculation method of the degree of normality is introduced. Finally, the examples of the degree of normality are shown.