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2016•PubMedOpen access

Topological-Pattern-Based Recommendation of UMLS Concepts for National Cancer Institute Thesaurus.

Zhe He, Yan Chen, Sherri de Coronado, Katrina Piskorski, James Geller

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Abstract

The National Cancer Institute Thesaurus (NCIt) is a reference terminology used to support clinical, translational and basic research as well as administrative activities. As medical knowledge evolves, concepts that might be missing from a particular needed subdomain are regularly added to the NCIt. However, terminology development is known to be labor-intensive and error-prone. Therefore, cost-effective semi-automated methods for identifying potentially missing concepts would be useful to terminology curators. Previously, we have developed a structural method leveraging the native term mappings of the Unified Medical Language System to identify potential concepts in several of its source vocabularies to enrich the SNOMED CT. In this paper, we tested an analogous method for NCIt. Concepts from eight UMLS source terminologies were identified as possibilities to enrich NCIt's conceptual content.

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What this paper is about

The National Cancer Institute Thesaurus (NCIt) is a reference terminology used to support clinical, translational and basic research as well as administrative activities. As medical knowledge evolves, concepts that might be missing from a particular needed subdomain are regularly added to the NCIt. However, terminology development is known to be labor-intensive and error-prone. Therefore, cost-effective semi-automated methods for identifying potentially missing concepts would be useful to terminology curators. Previously, we have developed a structural method leveraging the native term mappings of the Unified Medical Language System to identify potential concepts in several of its source vocabularies to enrich the SNOMED CT. In this paper, we tested an analogous method for NCIt. Concepts from eight UMLS source terminologies were identified as possibilities to enrich NCIt's conceptual content.

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Available abstract

The National Cancer Institute Thesaurus (NCIt) is a reference terminology used to support clinical, translational and basic research as well as administrative activities. As medical knowledge evolves, concepts that might be missing from a particular needed subdomain are regularly added to the NCIt. However, terminology development is known to be labor-intensive and error-prone. Therefore, cost-effective semi-automated methods for identifying potentially missing concepts would be useful to terminology curators. Previously, we have developed a structural method leveraging the native term mappings of the Unified Medical Language System to identify potential concepts in several of its source vocabularies to enrich the SNOMED CT. In this paper, we tested an analogous method for NCIt. Concepts from eight UMLS source terminologies were identified as possibilities to enrich NCIt's conceptual content.

Key concepts: Unified Medical Language System, Terminology, SNOMED CT, Thesaurus, Computer science, Information retrieval, Ontology, Systematized Nomenclature of Medicine

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Topological-Pattern-Based Recommendation of UMLS Concepts for National Cancer Institute Thesaurus. — Research Paper | ScholarLens