title: Combining lexical and semantic methods of inter-terminology mapping using the UMLS.
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.
authors.affiliation: National Library of Medicine, Bethesda, Maryland 20894, USA. kwfung@nlm.nih.gov
authors.forename: Kin Wah
authors.initials: KW
authors.lastname: Fung
authors.forename: Olivier
authors.initials: O
authors.lastname: Bodenreider
authors.forename: Alan R
authors.initials: AR
authors.lastname: Aronson
authors.forename: William T
authors.initials: WT
authors.lastname: Hole
authors.forename: Suresh
authors.initials: S
authors.lastname: Srinivasan
mesh_terms: D000465:Algorithms; D038801:International Classification of Diseases; D012660:Semantics; D017432:Unified Medical Language System; D018875:Vocabulary, Controlled