Linked Life Data

15492037

Source:http://linkedlifedata.com/resource/pubmed/id/15492037

Statements in which the resource exists.
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pubmed-article:15492037pubmed:abstractTextThe Digital Anatomist Foundational Model of Anatomy (FMA) is a large semantic network of more than 100,000 terms that refer to the anatomical entities, which together with 1.6 million structural relationships symbolically represent the physical organization of the human body. Evaluation of such a large knowledge base by domain experts is challenging because of the sheer size of the resource and the need to evaluate not just classes but also relationships. To meet this challenge, the authors have developed a relation-centric query interface, called Emily, that is able to query the entire range of classes and relationships in the FMA, yet is simple to use by a domain expert. Formative evaluation of this interface considered the ability of Emily to formulate queries based on standard anatomy examination questions, as well as the processing speed of the query engine. Results show that Emily is able to express 90% of the examination questions submitted to it and that processing time is generally 1 second or less, but can be much longer for complex queries. These results suggest that Emily will be a very useful tool, not only for evaluating the FMA, but also for querying and evaluating other large semantic networks.lld:pubmed
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pubmed-article:15492037pubmed:authorpubmed-author:RosseCorneliu...lld:pubmed
pubmed-article:15492037pubmed:authorpubmed-author:ShapiroLinda...lld:pubmed
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pubmed-article:15492037pubmed:pagination35-46lld:pubmed
pubmed-article:15492037pubmed:dateRevised2011-8-1lld:pubmed
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pubmed-article:15492037pubmed:articleTitleProcesses and problems in the formative evaluation of an interface to the Foundational Model of Anatomy knowledge base.lld:pubmed
pubmed-article:15492037pubmed:affiliationStructural Informatics Group, Department of Medical Education and Biomedical Informatics, Box 352350, Computer Science and Engineering, 634 Paul Allen Center, University of Washington, Seattle, WA 98195, USA. shapiro@cs.washington.edulld:pubmed
pubmed-article:15492037pubmed:publicationTypeJournal Articlelld:pubmed
pubmed-article:15492037pubmed:publicationTypeResearch Support, U.S. Gov't, P.H.S.lld:pubmed
pubmed-article:15492037pubmed:publicationTypeEvaluation Studieslld:pubmed
pubmed-article:15492037pubmed:publicationTypeResearch Support, N.I.H., Extramurallld:pubmed
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