| MedSynDiKATe--design considerations for an ontology-based medical text understanding system. | |
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MedLine Citation:
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PMID: 11079899 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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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. |
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Authors:
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U Hahn; M Romacker; S Schulz |
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Publication Detail:
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Type: Journal Article; Research Support, Non-U.S. Gov't |
Journal Detail:
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Title: Proceedings / AMIA ... Annual Symposium. AMIA Symposium Volume: - ISSN: 1531-605X ISO Abbreviation: Proc AMIA Symp Publication Date: 2000 |
Date Detail:
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Created Date: 2001-01-10 Completed Date: 2001-03-08 Revised Date: 2009-11-18 |
Medline Journal Info:
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Nlm Unique ID: 100883449 Medline TA: Proc AMIA Symp Country: United States |
Other Details:
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Languages: eng Pagination: 330-4 Citation Subset: IM |
Affiliation:
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Freiburg University, Text Knowledge Engineering Lab. |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Evaluation Studies as Topic Medical Records* Natural Language Processing* Software Unified Medical Language System |
| Comments/Corrections | |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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