Bin Nie, Jianqiang Du, Guoliang Xu, Riyue Yu, Zhuo Wang, Hongnin Liu, Bingtao Li
{"title":"基于OSC-OPLS/O2PLS-DA的中药性质分类与判别","authors":"Bin Nie, Jianqiang Du, Guoliang Xu, Riyue Yu, Zhuo Wang, Hongnin Liu, Bingtao Li","doi":"10.1109/IFITA.2010.190","DOIUrl":null,"url":null,"abstract":"the research for Chinese herbs’ warm and cold natures classification is a significative thing for clinical. The paper put forward a new model classification and discrimination for Traditional Chinese medicine(TCM)' nature based on orthogonal signal correction-orthogonal partial least squares-discriminant analysis (OSC-OPLS/O2PLS-DA) after normalization. The first, data preprocessing and normalization for the metabolites sample space’s data, and the results data 135 multiply 839 dimension consist of three sections: warm nature’s normalization sample, cold nature’s normalization sample, blank group normalization sample; The second, OSC, dimension reduction and noise reduction for the metabolites sample space’s data; the third, OPLS/O2PLS-DA, Generate classification and discrimination Method for Traditional Chinese medicine(TCM)' nature. The model was proved to be feasible and effective after tested with 6 type’s warm nature’s herbs, 6 type’s cold nature’s herbs.","PeriodicalId":393802,"journal":{"name":"2010 International Forum on Information Technology and Applications","volume":"90 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Classification and Discrimination for Traditional Chinese Medicine Nature Based on OSC-OPLS/O2PLS-DA\",\"authors\":\"Bin Nie, Jianqiang Du, Guoliang Xu, Riyue Yu, Zhuo Wang, Hongnin Liu, Bingtao Li\",\"doi\":\"10.1109/IFITA.2010.190\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"the research for Chinese herbs’ warm and cold natures classification is a significative thing for clinical. The paper put forward a new model classification and discrimination for Traditional Chinese medicine(TCM)' nature based on orthogonal signal correction-orthogonal partial least squares-discriminant analysis (OSC-OPLS/O2PLS-DA) after normalization. The first, data preprocessing and normalization for the metabolites sample space’s data, and the results data 135 multiply 839 dimension consist of three sections: warm nature’s normalization sample, cold nature’s normalization sample, blank group normalization sample; The second, OSC, dimension reduction and noise reduction for the metabolites sample space’s data; the third, OPLS/O2PLS-DA, Generate classification and discrimination Method for Traditional Chinese medicine(TCM)' nature. The model was proved to be feasible and effective after tested with 6 type’s warm nature’s herbs, 6 type’s cold nature’s herbs.\",\"PeriodicalId\":393802,\"journal\":{\"name\":\"2010 International Forum on Information Technology and Applications\",\"volume\":\"90 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-07-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Forum on Information Technology and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IFITA.2010.190\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Forum on Information Technology and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IFITA.2010.190","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Classification and Discrimination for Traditional Chinese Medicine Nature Based on OSC-OPLS/O2PLS-DA
the research for Chinese herbs’ warm and cold natures classification is a significative thing for clinical. The paper put forward a new model classification and discrimination for Traditional Chinese medicine(TCM)' nature based on orthogonal signal correction-orthogonal partial least squares-discriminant analysis (OSC-OPLS/O2PLS-DA) after normalization. The first, data preprocessing and normalization for the metabolites sample space’s data, and the results data 135 multiply 839 dimension consist of three sections: warm nature’s normalization sample, cold nature’s normalization sample, blank group normalization sample; The second, OSC, dimension reduction and noise reduction for the metabolites sample space’s data; the third, OPLS/O2PLS-DA, Generate classification and discrimination Method for Traditional Chinese medicine(TCM)' nature. The model was proved to be feasible and effective after tested with 6 type’s warm nature’s herbs, 6 type’s cold nature’s herbs.