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Biomedical subjects

Stuart J Nelson

Publications and source records attributed to Stuart J Nelson.

6 recordsLinked to original sources
PubMed2005

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 (Spearman's 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.

Semantics↗
PubMed2004

The MeSH translation maintenance system: structure, interface design, and implementation.

The National Library of Medicine (NLM) produces annual editions of the Medical Subject Headings (MeSH). Translations of MeSH are often done to make the vocabulary useful for non-English users. However, MeSH translators have encountered difficulties with entry vocabulary as they maintain and update their translation. Tracking MeSH changes and updating their translations in a reasonable time frame is cumbersome. NLM has developed and implemented a concept-centered vocabulary maintenance system for MeSH. This system has been extended to create an interlingual database of translations, the MeSH Translation Maintenance System (MTMS). This database allows continual updating of the translations, as well as facilitating tracking of the changes within MeSH from one year to another. The MTMS interface uses a Web-based design with multiple colors and fonts to indicate concepts needing translation or review. Concepts for which there is no exact English equivalent can be added. The system software encourages compliance with the Unicode standard in order to ensure that character sets with native alphabets and full orthography are used consistently.

Databases as Topic↗
PubMed2002

A semantic normal form for clinical drugs in the UMLS: early experiences with the VANDF.

A semantic normal form (SNF) for a clinical drug, designed to represent the meaning of an expression typically seen in a practitioner's medication order, has been developed and is being created in the UMLS Metathesaurus. The long term goal is to establish a relationship for every concept in the Metathesaurus with semantic type "clinical drug" with one or more of these semantic normal forms. First steps have been taken using the Veterans Administration National Drug File (VANDF). 70% of the entries in the VANDF could be parsed algorithmically into the SNF. Next steps include parsing other drug vocabularies included in the UMLS Metathesaurus and performing human review of the parsed vocabularies. After machine parsed forms have been merged in the Metathesaurus Information Database (MID), editors will be able to edit matched SNFs for accuracy and establish relationships and relationship attributes with other clinical drug concepts.

Algorithms↗
PubMed2002

Tracking meaning over time in the UMLS Metathesaurus.

The Unified Medical Language System(R) (UMLS) Metathesaurus contains records arranged by concept or meaning. Each concept contains a unique identifier (CUI) that can be used to track the concept over time. Since the January 2001 release, the Metathesaurus has included the file MRCUI that contains mappings for CUIs that disappear. This paper describes the processes that facilitated this effort and the ongoing effort to find suitable mappings for concepts whose meanings no longer exist in the Metathesaurus. This study highlights the need to identify missed synonymy prior to a release. It also shows a need to work more closely with source providers to identify the closest match in the Metathesaurus when they eliminate terms from their vocabularies.

National Library of Medicine (U.S.)↗