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Preliminary Analysis of Difficulty of Importing Pattern-Based Concepts into the National Cancer Institute Thesaurus

Maintenance of biomedical ontologies is difficult. We have developed a pattern-based method for dealing with the problem of identifying missing concepts in the National Cancer Institute thesaurus (NCIt). Specifically, we are mining patterns connecting NCIt concepts with concepts in other ontologies...

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Detalles Bibliográficos
Autores principales: HE, Zhe, GELLER, James
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5785234/
https://www.ncbi.nlm.nih.gov/pubmed/27577410
Descripción
Sumario:Maintenance of biomedical ontologies is difficult. We have developed a pattern-based method for dealing with the problem of identifying missing concepts in the National Cancer Institute thesaurus (NCIt). Specifically, we are mining patterns connecting NCIt concepts with concepts in other ontologies to identify candidate missing concepts. However, the final decision about a concept insertion is always up to a human ontology curator. In this paper, we are estimating the difficulty of this task for a domain expert by counting possible choices for a pattern-based insertion. We conclude that even with support of our mining algorithm, the insertion task is challenging.