• DocumentCode
    1788090
  • Title

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

  • Author

    Lianas, Luca ; Frexia, Francesca ; Delussu, Giovanni ; Anedda, Paolo ; Zanetti, Gianluigi

  • Author_Institution
    CRS4, Pula, Italy
  • fYear
    2014
  • fDate
    15-18 Oct. 2014
  • Firstpage
    370
  • Lastpage
    374
  • 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.
  • Keywords
    SQL; medical computing; NoSQL technologies; biomedical research projects; clinical data descriptions; clinical data management systems; next-generation SQL; openEHR formalisms; phenotypic data management systems; pyEHR; scalable clinical data management toolkit; storage back-ends; Computer architecture; Conferences; Databases; Engines; Informatics; Semantics; Terminology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    e-Health Networking, Applications and Services (Healthcom), 2014 IEEE 16th International Conference on
  • Conference_Location
    Natal
  • Type

    conf

  • DOI
    10.1109/HealthCom.2014.7001871
  • Filename
    7001871