Text-to-query: dynamically building structured analytics to illustrate textual content
Proceedings of the 2010 EDBT/ICDT Workshops
Graph-based concept identification and disambiguation for enterprise search
Proceedings of the 19th international conference on World wide web
Expressive and flexible access to web-extracted data: a keyword-based structured query language
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Survey of data management and analysis in disaster situations
Journal of Systems and Software
Intelligent personal health record: experience and open issues
Proceedings of the 1st ACM International Health Informatics Symposium
Automatic Home Medical Product Recommendation
Journal of Medical Systems
Challenges and communities of medical informatics research
ACM SIGMOD Record
An ontology-based similarity measure for biomedical data - Application to radiology reports
Journal of Biomedical Informatics
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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 associate 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.