Towards a mixed approach to extract biomedical terms from documents

Abstract : The proposed work aims at automatically extracting biomedical terms from free text. We present new extraction methods taking into account linguistic patterns specialized for the biomedical field, statistic term extraction measures such as C-value and statistic keyword extraction measures such as Okapi BM25, and TFIDF. These measures are combined in order to improve the extraction process and we investigate which combinations are the more relevant associated to different contexts. Experimental results show that an appropriate harmonic mean of C-value associated to keyword extraction measures offers better precision, both for single-word and multi-words term extraction. Experiments describe the extraction of English and French biomedical terms from a corpus of laboratory tests available online. The results are validated by using UMLS (in English) and only MeSH (in French) as reference.
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00859846
Contributor : Juan Antonio Lossio Ventura <>
Submitted on : Monday, September 9, 2013 - 3:36:33 PM
Last modification on : Thursday, May 24, 2018 - 3:59:23 PM
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Juan Antonio Lossio-Ventura, Clement Jonquet, Mathieu Roche, Maguelonne Teisseire. Towards a mixed approach to extract biomedical terms from documents. Knowledge Discovery in Bioinformatics, IGI Global, 2014, 4 (1), pp.15. ⟨10.4018/ijkdb.2014010101⟩. ⟨lirmm-00859846v1⟩

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