{"title":"检测阿托伐他汀药物的不良反应","authors":"Yihui Liu, U. Aickelin","doi":"10.1109/ISCID.2012.61","DOIUrl":null,"url":null,"abstract":"Adverse drug reaction (ADR) is widely concerned for public health issue. in this study we propose an original approach to detect the ADRs using feature matrix and feature selection. the experiments are carried out on the drug Atorvastatin. Major side effects for the drug are detected and better performance is achieved compared to other computerized methods. the detected ADRs are based on the computerized method, further investigation is needed.","PeriodicalId":246432,"journal":{"name":"2012 Fifth International Symposium on Computational Intelligence and Design","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Detect Adverse Drug Reactions for Drug Atorvastatin\",\"authors\":\"Yihui Liu, U. Aickelin\",\"doi\":\"10.1109/ISCID.2012.61\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Adverse drug reaction (ADR) is widely concerned for public health issue. in this study we propose an original approach to detect the ADRs using feature matrix and feature selection. the experiments are carried out on the drug Atorvastatin. Major side effects for the drug are detected and better performance is achieved compared to other computerized methods. the detected ADRs are based on the computerized method, further investigation is needed.\",\"PeriodicalId\":246432,\"journal\":{\"name\":\"2012 Fifth International Symposium on Computational Intelligence and Design\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Fifth International Symposium on Computational Intelligence and Design\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCID.2012.61\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Fifth International Symposium on Computational Intelligence and Design","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCID.2012.61","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detect Adverse Drug Reactions for Drug Atorvastatin
Adverse drug reaction (ADR) is widely concerned for public health issue. in this study we propose an original approach to detect the ADRs using feature matrix and feature selection. the experiments are carried out on the drug Atorvastatin. Major side effects for the drug are detected and better performance is achieved compared to other computerized methods. the detected ADRs are based on the computerized method, further investigation is needed.
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