pyEHR:用于生物医学研究项目的可扩展临床数据管理工具包

2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom) Pub Date : 2014-10-01 DOI:10.1109/HealthCom.2014.7001871

L. Lianas, F. Frexia, G. Delussu, Paolo Anedda, G. Zanetti

{"title":"pyEHR:用于生物医学研究项目的可扩展临床数据管理工具包","authors":"L. Lianas, F. Frexia, G. Delussu, Paolo Anedda, G. Zanetti","doi":"10.1109/HealthCom.2014.7001871","DOIUrl":null,"url":null,"abstract":"In this work we describe pyEHR, a new toolkit for building scalable clinical/phenotypic data management systems for biomedical research applications. The toolkit uses openEHR formalisms to guarantee the decoupling of clinical data descriptions from implementation details, and NoSQL technologies, or next-generation SQL ones, to provide scalable storage back-ends.","PeriodicalId":269964,"journal":{"name":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"pyEHR: A scalable clinical data management toolkit for biomedical research projects\",\"authors\":\"L. Lianas, F. Frexia, G. Delussu, Paolo Anedda, G. Zanetti\",\"doi\":\"10.1109/HealthCom.2014.7001871\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work we describe pyEHR, a new toolkit for building scalable clinical/phenotypic data management systems for biomedical research applications. The toolkit uses openEHR formalisms to guarantee the decoupling of clinical data descriptions from implementation details, and NoSQL technologies, or next-generation SQL ones, to provide scalable storage back-ends.\",\"PeriodicalId\":269964,\"journal\":{\"name\":\"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HealthCom.2014.7001871\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HealthCom.2014.7001871","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 1

摘要

在这项工作中，我们描述了pyEHR，一个为生物医学研究应用程序构建可扩展的临床/表型数据管理系统的新工具包。该工具包使用openEHR形式化来保证临床数据描述与实现细节的解耦，并使用NoSQL技术或下一代SQL技术来提供可扩展的存储后端。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

pyEHR: A scalable clinical data management toolkit for biomedical research projects

In this work we describe pyEHR, a new toolkit for building scalable clinical/phenotypic data management systems for biomedical research applications. The toolkit uses openEHR formalisms to guarantee the decoupling of clinical data descriptions from implementation details, and NoSQL technologies, or next-generation SQL ones, to provide scalable storage back-ends.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom)

自引率

0.00%

发文量