{"title":"基于支持向量机的计算机虹膜学心脏疾病检测","authors":"L. Permatasari, Astri Novianty, T. Purboyo","doi":"10.1109/ICCEREC.2016.7814983","DOIUrl":null,"url":null,"abstract":"Human iris can be used for detecting organ disorders based on iridology science. Nowadays, iridology diagnosis can be done automatically by computer using artificial intelligence approach. This research focused on cardiac diagnosis based on left iris map on clockwise direction around 2:00 to 3:00. The Principal Component Analysis (PCA) is used for feature extraction while the Support Vector Machine (SVM) for classification. Experimental results showed that the highest accuracy of classification is 80% for the classification.","PeriodicalId":431878,"journal":{"name":"2016 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Heart disorder detection based on computerized iridology using support vector machine\",\"authors\":\"L. Permatasari, Astri Novianty, T. Purboyo\",\"doi\":\"10.1109/ICCEREC.2016.7814983\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Human iris can be used for detecting organ disorders based on iridology science. Nowadays, iridology diagnosis can be done automatically by computer using artificial intelligence approach. This research focused on cardiac diagnosis based on left iris map on clockwise direction around 2:00 to 3:00. The Principal Component Analysis (PCA) is used for feature extraction while the Support Vector Machine (SVM) for classification. Experimental results showed that the highest accuracy of classification is 80% for the classification.\",\"PeriodicalId\":431878,\"journal\":{\"name\":\"2016 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCEREC.2016.7814983\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCEREC.2016.7814983","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Heart disorder detection based on computerized iridology using support vector machine
Human iris can be used for detecting organ disorders based on iridology science. Nowadays, iridology diagnosis can be done automatically by computer using artificial intelligence approach. This research focused on cardiac diagnosis based on left iris map on clockwise direction around 2:00 to 3:00. The Principal Component Analysis (PCA) is used for feature extraction while the Support Vector Machine (SVM) for classification. Experimental results showed that the highest accuracy of classification is 80% for the classification.