{"title":"临床决策支持系统中鉴别诊断列表的层次表示","authors":"T. Okumura, Masaki Tagawa","doi":"10.4108/icst.pervasivehealth.2014.255785","DOIUrl":null,"url":null,"abstract":"Clinical decision support systems (CDSSs) can generate differential diagnosis lists that may contain hundreds of diseases. These lists grow in size as coverage expands to rare diseases, but large lists can easily become a burden on user cognition. To address this issue, we first outline the representations of differential diagnosis lists on current CDSSs, and then propose a novel approach that represents these differential diagnosis lists hierarchically, coupled with an algorithm for optimal initialization. Preliminary evaluation suggested that our proposed approach outperforms existing approaches with respect to search costs, particularly for large lists. This hierarchical representation should alleviate the cognitive load on user physicians and provide an efficient means to search through very large lists.","PeriodicalId":120856,"journal":{"name":"Proceedings of the 8th International Conference on Pervasive Computing Technologies for Healthcare","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Hierarchical representation of differential diagnosis lists for clinical decision support systems\",\"authors\":\"T. Okumura, Masaki Tagawa\",\"doi\":\"10.4108/icst.pervasivehealth.2014.255785\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Clinical decision support systems (CDSSs) can generate differential diagnosis lists that may contain hundreds of diseases. These lists grow in size as coverage expands to rare diseases, but large lists can easily become a burden on user cognition. To address this issue, we first outline the representations of differential diagnosis lists on current CDSSs, and then propose a novel approach that represents these differential diagnosis lists hierarchically, coupled with an algorithm for optimal initialization. Preliminary evaluation suggested that our proposed approach outperforms existing approaches with respect to search costs, particularly for large lists. This hierarchical representation should alleviate the cognitive load on user physicians and provide an efficient means to search through very large lists.\",\"PeriodicalId\":120856,\"journal\":{\"name\":\"Proceedings of the 8th International Conference on Pervasive Computing Technologies for Healthcare\",\"volume\":\"60 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-05-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 8th International Conference on Pervasive Computing Technologies for Healthcare\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4108/icst.pervasivehealth.2014.255785\",\"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 8th International Conference on Pervasive Computing Technologies for Healthcare","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4108/icst.pervasivehealth.2014.255785","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hierarchical representation of differential diagnosis lists for clinical decision support systems
Clinical decision support systems (CDSSs) can generate differential diagnosis lists that may contain hundreds of diseases. These lists grow in size as coverage expands to rare diseases, but large lists can easily become a burden on user cognition. To address this issue, we first outline the representations of differential diagnosis lists on current CDSSs, and then propose a novel approach that represents these differential diagnosis lists hierarchically, coupled with an algorithm for optimal initialization. Preliminary evaluation suggested that our proposed approach outperforms existing approaches with respect to search costs, particularly for large lists. This hierarchical representation should alleviate the cognitive load on user physicians and provide an efficient means to search through very large lists.