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Combining lexical and semantic methods of inter-terminology mapping using the UMLS
Kin Wah Fung1, Olivier Bodenreider, Alan R Aronson
1National Library of Medicine, Bethesda, Maryland 20894, USA. kwfung@nlm.nih.gov
Studies in Health Technology and Informatics
|October 4, 2007
Summary
Mapping biomedical terms from SNOMED CT to ICD9CM is crucial for data reuse. Combining semantic and lexical mapping methods significantly improved accuracy and coverage for this inter-terminology task.
Area of Science:
- Biomedical Informatics
- Medical Terminology Management
- Health Data Interoperability
Background:
- Increasing volumes of electronic health data necessitate effective methods for re-using information.
- Inter-terminology mapping is essential for integrating diverse biomedical datasets.
Purpose of the Study:
- To develop and evaluate methods for mapping terms from SNOMED CT to ICD9CM.
- To compare the performance of semantic and lexical mapping approaches.
- To create a combined mapping strategy for enhanced accuracy.
Main Methods:
- Utilized the Unified Medical Language System (UMLS) as a knowledge base.
- Generated semantically-based and lexically-based mappings from SNOMED CT to ICD9CM.
- Compared mapping results against a gold standard dataset.
- Developed a combined mapping method based on sub-category precision.
Main Results:
- Semantic mapping demonstrated superior performance over lexical mapping in coverage, recall, and precision.
- The combined mapping method achieved 91% coverage, 43% recall, and 27% precision.
- The combined approach outperformed individual semantic and lexical methods.
Conclusions:
- Combining semantic and lexical mapping strategies offers a robust approach for inter-terminology mapping.
- The developed method can be customized to optimize performance for specific tasks.
- Effective terminology mapping enhances the utility and re-usability of biomedical data.
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