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A knowledge-based approach for retrieving scenario-specific medical text documents
Wesley W. Chu Ph.D.
Zhenyu Y. Liu Ph.D., University of California, Los Angeles
Wenlei Mao Ph.D.
Qinghua Zou Ph.D.
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ABSTRACT: Medical free-text queries often share the same scenario. A scenario represents a repeating task in healthcare. For example, a specific scenario is searching for treatment methods for a specific disease, where "treatment" is a term indicating the scenario. To support scenario-specific retrieval, in this paper we present a new knowledge-based approach to address these problems. In addition, we describe a testbed system developed using the approach. Our specific implementation uses the UMLS Metathesaurus and semantic structure to extract key concepts from a free text. The approach uses phrase-based indexing to represent similar concepts, and query expansion to improve matching query terms with the terms in the document. The system formulates the query based on the user's input and the
selected scenario template such as "disease, treatment" or "disease, diagnosis." Thus, it is able to retrieve documents relevant to the specific scenario. Evaluating the system using the standard OSHMED corpus, our empirical results validate the effectiveness of this new approach over the traditional text retrieval techniques. (c) 2005 Elsevier Ltd. All rights reserved.
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REQUIRED PUBLISHER STATEMENT:
Wesley W. Chu Ph.D., Zhenyu Y. Liu Ph.D., Wenlei Mao Ph.D., and Qinghua Zou Ph.D.,
"A knowledge-based approach for retrieving scenario-specific medical text documents"
(2005).
Control Engineering Practice.
13 (9),
pp. 1105-1121.
Postprint available free at: http://repositories.cdlib.org/postprints/1071
The original publication is available in Control Engineering Practice.
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