Literature DB >> 24788260

Mapping of biomedical text to concepts of lexicons, terminologies, and ontologies.

Michael Bada1.   

Abstract

Concept mapping is a fundamental task in biomedical text mining in which textual mentions of concepts of interest are annotated with specific entries of lexicons, terminologies, ontologies, or databases representing these concepts. Though there has been a significant amount of research, there are still a limited number of practical, publicly available tools for concept mapping of biomedical text specified by the user as an independent task. In this chapter, several tools that can automatically map biomedical text to concepts from a wide range of terminological resources are presented, followed by those that can map to more restricted sets of these resources. This presentation is intended to serve as a guide to researchers without a background in biomedical concept mapping of text for the selection of an appropriate tool based on usability, scalability, configurability, balance between precision and recall, and the desired set of terminological resources with which to annotate the text. Only with effective automatic concept-mapping tools will systems be able to scalably analyze the biomedical literature and other large sets of documents as a fundamental part of more complex text-mining tasks such as information extraction and hypothesis evaluation and generation.

Mesh:

Year:  2014        PMID: 24788260     DOI: 10.1007/978-1-4939-0709-0_3

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  6 in total

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Authors:  Tudor Groza; Karin Verspoor
Journal:  PLoS One       Date:  2015-03-19       Impact factor: 3.240

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Authors:  Sung-Pil Choi
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4.  Named entity linking of geospatial and host metadata in GenBank for advancing biomedical research.

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Journal:  Database (Oxford)       Date:  2017-01-01       Impact factor: 3.451

5.  DES-ROD: Exploring Literature to Develop New Links between RNA Oxidation and Human Diseases.

Authors:  Magbubah Essack; Adil Salhi; Christophe Van Neste; Arwa Bin Raies; Faroug Tifratene; Mahmut Uludag; Arnaud Hungler; Bozidarka Zaric; Sonja Zafirovic; Takashi Gojobori; Esma Isenovic; Vladan P Bajic
Journal:  Oxid Med Cell Longev       Date:  2020-03-27       Impact factor: 6.543

6.  Gold-standard ontology-based anatomical annotation in the CRAFT Corpus.

Authors:  Michael Bada; Nicole Vasilevsky; William A Baumgartner; Melissa Haendel; Lawrence E Hunter
Journal:  Database (Oxford)       Date:  2017-01-01       Impact factor: 3.451

  6 in total

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