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The SINAMED and ISIS Projects: Applying Text Mining Techniques to Improve Access to a Medical Digital Library

  • Manuel de Buenaga
  • Manuel Maña
  • Diego Gachet
  • Jacinto Mata
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4172)

Abstract

Intelligent information access systems integrate text mining and content analysis capabilities as a relevant element in an increasing way. In this paper we present our work focused on the integration of text categorization and summarization to improve information access on a specific medical domain, patient clinical records and related scientific documentation, in the framework of two different research projects: SINAMED and ISIS, developed by a consortium of two research groups from two universities, one hospital and one software development firm. SINAMED has a basic research orientation and its goal is to design new text categorization and summarization algorithms based on the utilization of lexical resources in the biomedical domain. ISIS is a R&D project with a more applied and technology-transfer orientation, focused on more direct practical aspects of the utilization in a concrete public health institution.

Keywords

Text Categorization Unify Medical Language System Biomedical Domain European Regional Development Fund Text Summarization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Manuel de Buenaga
    • 1
  • Manuel Maña
    • 2
  • Diego Gachet
    • 1
  • Jacinto Mata
    • 2
  1. 1.Universidad Europea de Madrid – Escuela Superior PolitécnicaVillaviciosa de Odón, MadridEspaña
  2. 2.Dpto. Ing. Electrón., Sistemas Informáticos y Aut., Escuela Politécnica SuperiorUniversidad de HuelvaPalos de la Frontera, HuelvaEspaña

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