L. Lianas, F. Frexia, G. Delussu, Paolo Anedda, G. Zanetti
{"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}
引用次数: 1
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.
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