Document Detail


Semantic structuring of and information extraction from medical documents using the UMLS.
MedLine Citation:
PMID:  18852916     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
OBJECTIVES: This paper introduces SeReMeD (Semantic Representation of Medical Documents), a method for automatically generating knowledge representations from natural language documents. The suitability of the Unified Medical Language System (UMLS) as domain knowledge for this method is analyzed. METHODS: SeReMeD combines existing language engineering methods and semantic transformation rules for mapping syntactic information to semantic roles. In this way, the relevant content of medical documents is mapped to semantic structures. In order to extract specific data, these semantic structures are searched for concepts and semantic roles. A study is carried out that uses SeReMeD to detect specific data in medical narratives such as documented diagnoses or procedures. RESULTS: The system is tested on chest X-ray reports. In first evaluations of the system's performance, the generation of semantic structures achieves a correctness of 80%, whereas the extraction of documented findings obtains values of 93% precision and 83% recall. CONCLUSIONS: The results suggest that the methods described here can be used to accurately extract data from medical narratives, although there is also some potential for improving the results. The proposed methods provide two main benefits. By using existing language engineering methods, the effort required to construct a medical information extraction system is reduced. It is also possible to change the domain knowledge and therefore to create a more (or less) specialized system, capable of handling various medical sub-domains.
Authors:
K Denecke
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Methods of information in medicine     Volume:  47     ISSN:  0026-1270     ISO Abbreviation:  Methods Inf Med     Publication Date:  2008  
Date Detail:
Created Date:  2008-10-14     Completed Date:  2008-12-19     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0210453     Medline TA:  Methods Inf Med     Country:  Germany    
Other Details:
Languages:  eng     Pagination:  425-34     Citation Subset:  IM    
Affiliation:
Research Center L3S, Appelstrasse 9a, 30167 Hanover, Germany. denecke@L3S.de
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MeSH Terms
Descriptor/Qualifier:
Information Storage and Retrieval / methods*
Medical Informatics
Semantics*
Unified Medical Language System*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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