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
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;
Conference_Titel :
e-Health Networking, Applications and Services (Healthcom), 2014 IEEE 16th International Conference on
Conference_Location :
Natal
DOI :
10.1109/HealthCom.2014.7001871
