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Designing a Concept-Mining Model for the Extraction of Medical Information in Spanish

Designing a Concept-Mining Model for the Extraction of Medical Information in Spanish
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Author(s): Olga Acosta (Singularyta SpA, Chile) and César Aguilar (Pontificia Universidad Católica de Chile, Chile)
Copyright: 2021
Pages: 17
Source title: Encyclopedia of Information Science and Technology, Fifth Edition
Source Author(s)/Editor(s): Mehdi Khosrow-Pour D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-7998-3479-3.ch059

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Abstract

This article sketches the development of a method for mining concepts applied on medical corpora in Spanish. Such method is based in the approach formulated by Ananiadou and McNaught, who give a special relevance to the need to create and use natural language processing (NLP) tools, in order to extract information from large collections of documents, such as PubMed (www.ncbi.nlm.nih.gov/pubmed/). Thanks to this repository, projects such as the Corpus Genia (www.geniaproject.org), the MEDIE search engine (www.nactem.ac.uk/medie/), which considers syntactic criteria and semantics to extract medical concepts, or the Open Biological and Biomedical Ontology Project (http://obofoundry.org/), which focuses on the development of ontologies that provide an organized knowledge system in biomedicine. Particularly, this proposal focused in two objectives: (1) the extraction of specialized terms and (2) the identification of lexical-semantic relationships, in concrete hyponymy/hypernymy and meronymy.

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