Automated knowledge extraction from the UMLS

This paper presents our work in extracting disease-chemical relationship knowledge from the UMLS Co-occurrence table (MRCOC) using an automated method. We evaluated the quality of the knowledge from UMLS MRCOC by comparing it with knowledge from other sources: For disease-lab chemical relationships,...

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Bibliographische Detailangaben
Veröffentlicht in:Proceedings. AMIA Symposium. - 1998. - (1998) vom: 13., Seite 568-72
1. Verfasser: Zeng, Q (VerfasserIn)
Weitere Verfasser: Cimino, J J
Format: Aufsatz
Sprache:English
Veröffentlicht: 1998
Zugriff auf das übergeordnete Werk:Proceedings. AMIA Symposium
Schlagworte:Journal Article Research Support, U.S. Gov't, P.H.S. Pharmaceutical Preparations
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245 1 0 |a Automated knowledge extraction from the UMLS 
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520 |a This paper presents our work in extracting disease-chemical relationship knowledge from the UMLS Co-occurrence table (MRCOC) using an automated method. We evaluated the quality of the knowledge from UMLS MRCOC by comparing it with knowledge from other sources: For disease-lab chemical relationships, knowledge was obtained from a decision support system (DXplain) and our own knowledge base of medical terminology (MED) through automated processes. For disease-drug chemical relationships, knowledge was manually acquired from the medical literature. Evaluations showed that the UMLS MRCOC knowledge has good sensitivity, especially regarding disease-drug relationships. We are using this knowledge to produce disease-specific views of patients' electronic patient record 
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