%0 Journal Article %1 Fung:2007qt %A Fung, K. W. %A Bodenreider, O. %A Aronson, A. R. %A Hole, W. T. %A Srinivasan, S. %D 2007 %J Stud Health Technol Inform %K Algorithms Classification Controlled Diseases International Language Medical Semantics System Unified Vocabulary, of %N Pt 1 %P 605-9 %T Combining lexical and semantic methods of inter-terminology mapping using the UMLS %V 129 %X The need for inter-terminology mapping is constantly increasing with the growth in the volume of electronically captured biomedical data and the demand to re-use the same data for secondary purposes. Using the UMLS as a knowledge base, semantically-based and lexically-based mappings were generated from SNOMED CT to ICD9CM terms and compared to a gold standard. Semantic mapping performed better than lexical mapping in terms of coverage, recall and precision. As the two mapping methods are orthogonal, the two sets of mappings can be used to validate and enhance each other. A method of combining the mappings based on the precision level of sub-categories in each method was derived. The combined method outperformed both methods, achieving coverage of 91%, recall of 43% and precision of 27%. It is also possible to customize the method of combination to optimize performance according to the task at hand.

@article{Fung:2007qt, abstract = {The need for inter-terminology mapping is constantly increasing with the growth in the volume of electronically captured biomedical data and the demand to re-use the same data for secondary purposes. Using the UMLS as a knowledge base, semantically-based and lexically-based mappings were generated from SNOMED CT to ICD9CM terms and compared to a gold standard. Semantic mapping performed better than lexical mapping in terms of coverage, recall and precision. As the two mapping methods are orthogonal, the two sets of mappings can be used to validate and enhance each other. A method of combining the mappings based on the precision level of sub-categories in each method was derived. The combined method outperformed both methods, achieving coverage of 91%, recall of 43% and precision of 27%. It is also possible to customize the method of combination to optimize performance according to the task at hand.}, added-at = {2012-06-02T05:59:56.000+0200}, author = {Fung, K. W. and Bodenreider, O. and Aronson, A. R. and Hole, W. T. and Srinivasan, S.}, biburl = {https://www.bibsonomy.org/bibtex/248b18aec8c4172eab097d585bcbbc895/ozborn}, date-added = {2012-06-01 16:59:33 -0500}, date-modified = {2012-06-01 16:59:49 -0500}, interhash = {009108644c138011df41148cbb4218c2}, intrahash = {48b18aec8c4172eab097d585bcbbc895}, journal = {Stud Health Technol Inform}, keywords = {Algorithms Classification Controlled Diseases International Language Medical Semantics System Unified Vocabulary, of}, note = {Fung, Kin Wah Bodenreider, Olivier Aronson, Alan R Hole, William T Srinivasan, Suresh Z99 LM999999/LM/NLM NIH HHS/United States Evaluation Studies Research Support, N.I.H., Intramural Netherlands Studies in health technology and informatics}, number = {Pt 1}, pages = {605-9}, timestamp = {2012-06-03T07:20:35.000+0200}, title = {Combining lexical and semantic methods of inter-terminology mapping using the UMLS}, volume = 129, year = 2007 }