{"title":"病案检索中的自适应证据加权方法","authors":"Dongqing Zhu, Ben Carterette","doi":"10.1145/2484028.2484175","DOIUrl":null,"url":null,"abstract":"In this paper, we present a medical record search system which is useful for identifying cohorts required in clinical studies. In particular, we propose a query-adaptive weighting method that can dynamically aggregate and score evidence in multiple medical reports (from different hospital departments or from different tests within the same department) of a patient. Furthermore, we explore several informative features for learning our retrieval model.","PeriodicalId":178818,"journal":{"name":"Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"An adaptive evidence weighting method for medical record search\",\"authors\":\"Dongqing Zhu, Ben Carterette\",\"doi\":\"10.1145/2484028.2484175\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present a medical record search system which is useful for identifying cohorts required in clinical studies. In particular, we propose a query-adaptive weighting method that can dynamically aggregate and score evidence in multiple medical reports (from different hospital departments or from different tests within the same department) of a patient. Furthermore, we explore several informative features for learning our retrieval model.\",\"PeriodicalId\":178818,\"journal\":{\"name\":\"Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval\",\"volume\":\"57 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-07-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2484028.2484175\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2484028.2484175","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An adaptive evidence weighting method for medical record search
In this paper, we present a medical record search system which is useful for identifying cohorts required in clinical studies. In particular, we propose a query-adaptive weighting method that can dynamically aggregate and score evidence in multiple medical reports (from different hospital departments or from different tests within the same department) of a patient. Furthermore, we explore several informative features for learning our retrieval model.