ArticleStudies in health technology and informatics2007
Lessons learned from cross-validating alignments between large anatomical ontologies.
Article in Studies in health technology and informatics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- A review of auditing techniques for the Unified Medical Language System.Journal of the American Medical Informatics Association : JAMIA · 2020Review
- Uberon, an integrative multi-species anatomy ontology.Genome biology · 2012Article
- Use artificial neural network to align biological ontologies.BMC genomics · 2008Article
- Identifying mismatches in alignments of large anatomical ontologies.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2007Article
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Authors and funding
2 authors.
Funding
Abstract
objectivesTo compare the alignments of two large anatomical ontologies (the Foundational Model of Anatomy and GALEN) produced by three ontology alignment systems (AOAS, FALCON and PRIOR) in the framework of the Ontology Alignment Evaluation Initiative during its 2006 campaign. MATERIALS: Number of mappings identified by AOAS: 3,132, FALCON: 2,518 and PRIOR: 2,589.
methodsThree approaches to analyzing and comparing the results were utilized: computing the overlap among result files, manual review of some 2,000 mappings and structural validation.
conclusionsThe generic systems FALCON and PRIOR identify many false positives and false negatives. With a stricter and domain-specific lexical similarity model, AOAS has a better precision, but is more sensitive to missing synonyms and misspellings.
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17911831PMC2408442What OpenQuestion holds
Registered trials
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