The integration of EMR with the mind of physicians has become an absolute priority in order to foster a meaningful use of Electronic Medical Records. This requires developing ontological solutions that allow integrating the categories physicians have in mind with the categories and objects integrated in the system.
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It was developed by:
-Regenstrief Institute, School of Medicine, and Center for Aging Research, Indiana University Indianapolis, Indiana
-IBM T.J. Watson Research Yorktown Heights, New York
-School of Computing and Information Sciences, Florida International University
“As the use of Electronic Medical Records (EMRs) becomes more widespread, so does the need for effective information discovery within them. Recently proposed EMR standards are XML-based. A key characteristic in these standards is the frequent use of ontological references, i.e., ontological concept codes appear as XML elements and are used to ssociate portions of the EMR document with concepts defined in a domain ontology. A rich corpus of work addresses searching XML documents. Unfortunately, these works do not make use of ontological references to enhance search. In this paper we present the XOntoRank system which addresses the problem of ontology-aware keyword search of XML documents with a particular focus on EMR XML documents. Our current prototypes and experiments use the Health Level Seven (HL7) Clinical Document Architecture (CDA) Release 2.0 standard of EMR representation and the Systematized Nomenclature of Human and Veterinary Medicine (SNOMED) ontology, although the presented techniques and results are applicable to any EMR hierarchical format and any ontology that defines concepts and relationships.”
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