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,...
| Veröffentlicht in: | Proceedings. AMIA Symposium. - 1998. - (1998) vom: 13., Seite 568-72 |
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| Format: | Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
1998
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| Zugriff auf das übergeordnete Werk: | Proceedings. AMIA Symposium |
| Schlagworte: | Journal Article Research Support, U.S. Gov't, P.H.S. Pharmaceutical Preparations |
| Zusammenfassung: | 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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| Beschreibung: | Date Completed 16.03.1999 Date Revised 13.11.2018 published: Print Citation Status MEDLINE |
| ISSN: | 1531-605X |