Text mining approaches for automated literature knowledge extraction and representation

Angelo Nuzzo, Francesca Mulas, Matteo Gabetta, Eloisa Arbustini, Blaž Zupan, Cristiana Larizza, Riccardo Bellazzi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Due to the overwhelming volume of published scientific papers, information tools for automated literature analysis are essential to support current biomedical research. We have developed a knowledge extraction tool to help researcher in discovering useful information which can support their reasoning process. The tool is composed of a search engine based on Text Mining and Natural Language Processing techniques, and an analysis module which process the search results in order to build annotation similarity networks. We tested our approach on the available knowledge about the genetic mechanism of cardiac diseases, where the target is to find both known and possible hypothetical relations between specific candidate genes and the trait of interest. We show that the system i) is able to effectively retrieve medical concepts and genes and ii) plays a relevant role assisting researchers in the formulation and evaluation of novel literature-based hypotheses.

Original languageEnglish
Title of host publicationStudies in Health Technology and Informatics
Pages954-958
Number of pages5
Volume160
EditionPART 1
DOIs
Publication statusPublished - 2010
Event13th World Congress on Medical and Health Informatics, Medinfo 2010 - Cape Town, South Africa
Duration: Sep 12 2010Sep 15 2010

Other

Other13th World Congress on Medical and Health Informatics, Medinfo 2010
CountrySouth Africa
CityCape Town
Period9/12/109/15/10

Keywords

  • Annotation networks
  • Candidate gene study
  • Gene ranking
  • Text Mining

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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  • Cite this

    Nuzzo, A., Mulas, F., Gabetta, M., Arbustini, E., Zupan, B., Larizza, C., & Bellazzi, R. (2010). Text mining approaches for automated literature knowledge extraction and representation. In Studies in Health Technology and Informatics (PART 1 ed., Vol. 160, pp. 954-958) https://doi.org/10.3233/978-1-60750-588-4-954