Document Detail


MedSynDiKATe--design considerations for an ontology-based medical text understanding system.
MedLine Citation:
PMID:  11079899     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
MedSynDiKATe is a natural language processor for automatically acquiring knowledge from medical finding reports. The content of these documents is transferred to formal representation structures which constitute a corresponding text knowledge base. The general system architecture we present integrates requirements from the analysis of single sentences, as well as those of referentially linked sentences forming cohesive texts. The strong demands MedSynDiKATe poses to the availability of expressive knowledge sources are accounted for by two alternative approaches to (semi)automatic ontology engineering.
Authors:
U Hahn; M Romacker; S Schulz
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Proceedings / AMIA ... Annual Symposium. AMIA Symposium     Volume:  -     ISSN:  1531-605X     ISO Abbreviation:  Proc AMIA Symp     Publication Date:  2000  
Date Detail:
Created Date:  2001-01-10     Completed Date:  2001-03-08     Revised Date:  2009-11-18    
Medline Journal Info:
Nlm Unique ID:  100883449     Medline TA:  Proc AMIA Symp     Country:  United States    
Other Details:
Languages:  eng     Pagination:  330-4     Citation Subset:  IM    
Affiliation:
Freiburg University, Text Knowledge Engineering Lab.
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MeSH Terms
Descriptor/Qualifier:
Evaluation Studies as Topic
Medical Records*
Natural Language Processing*
Software
Unified Medical Language System
Comments/Corrections

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