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Advanced Computational Intelligence Paradigms in Healthcare 5 pp 45–65Cite as

Data Mining Based on Intelligent Systems for Decision Support Systems in Healthcare

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 326))

Abstract

In this paper we make an extensive study of Artificial Intelligence (AI) techniques that can be used in decision support systems in healthcare. In particular, we propose variants of ensemble methods (i.e., Rotation Forest and Input Decimated Ensembles) that are based on perturbing features, and we make a wide comparison among the ensemble approaches. We illustrate the power of these techniques by applying our approaches to different healthcare problems. Included in this chapter is extensive background material on the single classifier systems, ensemble methods, and feature transforms used in the experimental section.

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Author information

Authors and Affiliations

  1. DEIS, IEIIT—CNR, Università di Bologna, Viale Risorgimento 2, 40136, Bologna, Italy

    Loris Nanni & Alessandra Lumini

  2. Computer Information Systems, Missouri State University, 901 S. National, Springfield, MO, 65804, USA

    Sheryl Brahnam & Tonya Barrier

Authors
  1. Loris Nanni
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  2. Sheryl Brahnam
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  3. Alessandra Lumini
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  4. Tonya Barrier
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Editor information

Editors and Affiliations

  1. Missouri State University, MO, USA

    Sheryl Brahnam

  2. University of South Australia, Adelaide, Australia

    Lakhmi C. Jain

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Nanni, L., Brahnam, S., Lumini, A., Barrier, T. (2010). Data Mining Based on Intelligent Systems for Decision Support Systems in Healthcare. In: Brahnam, S., Jain, L.C. (eds) Advanced Computational Intelligence Paradigms in Healthcare 5. Studies in Computational Intelligence, vol 326. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16095-0_4

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  • DOI: https://doi.org/10.1007/978-3-642-16095-0_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16094-3

  • Online ISBN: 978-3-642-16095-0

  • eBook Packages: EngineeringEngineering (R0)

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