{"title":"Linking the scientific and clinical data with KI2NA-LHC — An outline","authors":"V. Nováček, A. Naseer","doi":"10.1109/CBMS.2013.6627867","DOIUrl":null,"url":null,"abstract":"We introduce KI2NA-LHC (Linked Health Care) a system for data and knowledge integration in life sciences. In particular, we focus on linking clinical resources (electronic patient records) with scientific documents and data (research articles, biomedical ontologies and databases). Our motivation is two-fold. Firstly, we aim to instantly provide scientific context of particular patient cases for clinicians in order for them to propose treatments in a more informed way. Secondly, we want to build a technical infrastructure for researchers that will allow them to semi-automatically formulate and evaluate their hypothesis against longitudinal patient data. This paper outlines the proposed system and its services in a broader context of KI2NA, an ongoing collaboration between the DERI research institute and Fujitsu Laboratories.","PeriodicalId":20519,"journal":{"name":"Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems","volume":"48 1","pages":"540-541"},"PeriodicalIF":0.0000,"publicationDate":"2013-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CBMS.2013.6627867","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
We introduce KI2NA-LHC (Linked Health Care) a system for data and knowledge integration in life sciences. In particular, we focus on linking clinical resources (electronic patient records) with scientific documents and data (research articles, biomedical ontologies and databases). Our motivation is two-fold. Firstly, we aim to instantly provide scientific context of particular patient cases for clinicians in order for them to propose treatments in a more informed way. Secondly, we want to build a technical infrastructure for researchers that will allow them to semi-automatically formulate and evaluate their hypothesis against longitudinal patient data. This paper outlines the proposed system and its services in a broader context of KI2NA, an ongoing collaboration between the DERI research institute and Fujitsu Laboratories.
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