Suresh Srinivasan

Integrating SNOMED CT into the UMLS: An Exploration of Different Views of Synonymy and Quality of Editing

OBJECTIVE The integration of SNOMED CT into the Unified Medical Language System (UMLS) involved the alignment of two views of synonymy that were different because the two vocabulary systems have different intended purposes and editing principles. The UMLS is organized according to one view of synonymy, but its structure also represents all the individual views of synonymy present in its source vocabularies. Despite progress in knowledge-based automation of development and maintenance of vocabularies, manual curation is still the main method of determining synonymy. The aim of this study was to investigate the quality of human judgment of synonymy. DESIGN Sixty pairs of potentially controversial SNOMED CT synonyms were reviewed by 11 domain vocabulary experts (six UMLS editors and five noneditors), and scores were assigned according to the degree of synonymy. MEASUREMENTS The synonymy scores of each subject were compared to the gold standard (the overall mean synonymy score of all subjects) to assess accuracy. Agreement between UMLS editors and noneditors was measured by comparing the mean synonymy scores of editors to noneditors. RESULTS Average accuracy was 71% for UMLS editors and 75% for noneditors (difference not statistically significant). Mean scores of editors and noneditors showed significant positive correlation (Spearmans rank correlation coefficient 0.654, two-tailed p < 0.01) with a concurrence rate of 75% and an interrater agreement kappa of 0.43. CONCLUSION The accuracy in the judgment of synonymy was comparable for UMLS editors and nonediting domain experts. There was reasonable agreement between the two groups.

Adding neuronames to the UMLS metathesaurus

NeuroNames is a valuable component of the Metathesaurus, one Knowledge Source in the National Library of Medicine’s Unified Medical Language System (UMLS). The Metathesaurus organizes biomedical names from many component vocabularies by meaning, uniting those with the same meaning in concepts. The Spring 2002 release contains 2.1 million names for 871,584 Concepts from 102 sources. NeuroNames provides an authoritative reference vocabulary for neuroscience, with rich synonymy and valuable links to further information such as BrainInfo. Its very high standards permit quality assurance including the identification of unrecognized synonyms from other Metathesaurus vocabularies. The addition of NeuroNames enables navigation from many other vocabularies to NeuroNames and its linked resources, or from NeuroNames to other resources that use different vocabularies. The UMLS Metathesaurus