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Theory, empiricism and practice:Commentary on TBLT in ARAL 2016
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Automatic concept recognition using the Human Phenotype Ontology reference and test suite corpora
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Groza, Tudor; Köhler, Sebastian; Doelken, Sandra; Collier, Nigel; Oellrich, Anika; Smedley, Damian; Couto, Francisco M; Baynam, Gareth; Zankl, Andreas; Robinson, Peter N.. - : Oxford University Press, 2015
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Abstract:
Concept recognition tools rely on the availability of textual corpora to assess their performance and enable the identification of areas for improvement. Typically, corpora are developed for specific purposes, such as gene name recognition. Gene and protein name identification are longstanding goals of biomedical text mining, and therefore a number of different corpora exist. However, phenotypes only recently became an entity of interest for specialized concept recognition systems, and hardly any annotated text is available for performance testing and training. Here, we present a unique corpus, capturing text spans from 228 abstracts manually annotated with Human Phenotype Ontology (HPO) concepts and harmonized by three curators, which can be used as a reference standard for free text annotation of human phenotypes. Furthermore, we developed a test suite for standardized concept recognition error analysis, incorporating 32 different types of test cases corresponding to 2164 HPO concepts. Finally, three established phenotype concept recognizers (NCBO Annotator, OBO Annotator and Bio-LarK CR) were comprehensively evaluated, and results are reported against both the text corpus and the test suites. The gold standard and test suites corpora are available from http://bio-lark.org/hpo_res.html.
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Keyword:
Original Article
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URL: https://doi.org/10.1093/database/bav005
http://www.ncbi.nlm.nih.gov/pubmed/25725061
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4343077
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Learning to Perform Narrative Task: A Semester Long Study of Task Sequencing Effects
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Integrating the Human Phenotype Ontology into HeTOP Terminology-Ontology Server.
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In: ISSN: 0926-9630 ; EISSN: 1879-8365 ; Studies in Health Technology and Informatics ; https://www.hal.inserm.fr/inserm-00854299 ; Studies in Health Technology and Informatics, IOS Press, 2013, 192, pp.961 (2013)
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