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Quality-Based Knowledge Discovery from Medical Text on the Web

Example of Computational Methods in Web Intelligence

  • Chapter
Quality Issues in the Management of Web Information

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 50))

Abstract

The MEDLINE database (Medical Literature Analysis and Retrieval System Online) contains an enormously increasing volume of biomedical articles. Consequently there is need for techniques which enable the quality-based discovery, the extraction, the integration and the use of hidden knowledge in those articles. Text mining helps to cope with the interpretation of these large volumes of data. Co-occurrence analysis is a technique applied in text mining. Statistical models are used to evaluate the significance of the relationship between entities such as disease names, drug names, and keywords in titles, abstracts or even entire publications. In this paper we present a selection of quality-oriented Web-based tools for analyzing biomedical literature, and specifically discuss PolySearch, FACTA and Kleio. Finally we discuss Pointwise Mutual Information (PMI), which is a measure to discover the strength of a relationship. PMI provides an indication of how more often the query and concept co-occur than expected by change. The results reveal hidden knowledge in articles regarding rheumatic diseases indexed by MEDLINE, thereby exposing relationships that can provide important additional information for medical experts and researchers for medical decision-making and quality-enhancing.

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Authors and Affiliations

  1. Institute for Medical Informatics, Statistics and Documentation, Medical University Graz, Graz, Austria

    Andreas Holzinger, Michael Geier & Klaus-Martin Simonic

  2. Department of Computer Engineering, Okan University, Istanbul, Turkey

    Pinar Yildirim

Authors
  1. Andreas Holzinger
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  2. Pinar Yildirim
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  3. Michael Geier
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  4. Klaus-Martin Simonic
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Corresponding author

Correspondence to Andreas Holzinger .

Editor information

Editors and Affiliations

  1. Milano Bicocca, Dipartimento di Informatica, Universita' degli Studi di, Edificio U14, Viale Sarca 336, Milano, 20126, Italy

    Gabriella Pasi

  2. CNR IDPA Inst. f. Environmental, Process Dynamics, Italian National Research Council, Via Pasubio 5, Dalmine, 24044, Italy

    Gloria Bordogna

  3. , School of Electrical and Information, University of South Australia, Adelaide, 5095, South Australia, Australia

    Lakhmi C. Jain

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Holzinger, A., Yildirim, P., Geier, M., Simonic, KM. (2013). Quality-Based Knowledge Discovery from Medical Text on the Web. In: Pasi, G., Bordogna, G., Jain, L. (eds) Quality Issues in the Management of Web Information. Intelligent Systems Reference Library, vol 50. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37688-7_7

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  • DOI: https://doi.org/10.1007/978-3-642-37688-7_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37687-0

  • Online ISBN: 978-3-642-37688-7

  • eBook Packages: EngineeringEngineering (R0)

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