The SINAMED and ISIS Projects: Applying Text Mining Techniques to Improve Access to a Medical Digital Library
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.
KeywordsText Categorization Unify Medical Language System Biomedical Domain European Regional Development Fund Text Summarization
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- 1.Aronson, A.R., Mork, J.G., Gay, C.W., Humphrey, S.M., Rogers, W.J.: The NLM Indexing Initiative’s Medical Text Indexer. In: Proceedings of Medinfo, San Francisco (2004)Google Scholar
- 5.Elhadad, N., McKeown, K.R.: Towards generating patient specific summaries of medical articles. In: Proceedings of Automatic Summarization Workshop (NAACL), Pittsburgh, USA (2001)Google Scholar