{"title":"Health Data Representation through Web Semantic, a Case Study Applied to Electronic Records Medical in the UTPL Hospital","authors":"Mónica Calva, Nelson Piedra","doi":"10.1109/CLEI52000.2020.00040","DOIUrl":null,"url":null,"abstract":"Patient medical information is diverse, extensive and of high value in supporting informed medical decision-making. This information is highly complex, is distributed among different systems, presents high heterogeneity, is stored in different formats, and has different levels of structuring. The management of this information poses interoperability challenges in tasks related to data integration and reuse. In this work, an alternative is presented to face these challenges using semantic technologies. We propose to transform this heterogeneous, distributed, and unstructured information in a way that ensures high interoperability, reuse, and direct processing by machine agents. The pilot of this proposal was developed at the UTPL Hospital.","PeriodicalId":413655,"journal":{"name":"2020 XLVI Latin American Computing Conference (CLEI)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 XLVI Latin American Computing Conference (CLEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CLEI52000.2020.00040","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Patient medical information is diverse, extensive and of high value in supporting informed medical decision-making. This information is highly complex, is distributed among different systems, presents high heterogeneity, is stored in different formats, and has different levels of structuring. The management of this information poses interoperability challenges in tasks related to data integration and reuse. In this work, an alternative is presented to face these challenges using semantic technologies. We propose to transform this heterogeneous, distributed, and unstructured information in a way that ensures high interoperability, reuse, and direct processing by machine agents. The pilot of this proposal was developed at the UTPL Hospital.