XOntoRank: Ontology-Aware Search of Electronic Medical Records

被引:10
|
作者
Farfan, Fernando [1 ]
Hristidis, Vagelis [1 ]
Ranganathan, Anand [2 ]
Weiner, Michael [3 ,4 ]
机构
[1] Florida Int Univ, Sch Comp & Informat Sci, Miami, FL 33199 USA
[2] IBM Corp, Thomas J Watson Res Ctr, Yorktown Hts, NY 10598 USA
[3] Indiana Univ, Sch Med, Regntrif Inst, Indianapolis, IN 46204 USA
[4] Indiana Univ, Ctr Aging Res, Indianapolis, IN 46204 USA
来源
ICDE: 2009 IEEE 25TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING, VOLS 1-3 | 2009年
基金
美国国家科学基金会;
关键词
SEMANTIC SIMILARITY; XML;
D O I
10.1109/ICDE.2009.73
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
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.
引用
收藏
页码:820 / +
页数:3
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