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Applied Data Mining: From Biomarker Discovery to Decision Support Systems

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Computational Medicine

Abstract

This chapter provides an overview of emerging bioinformatics methods for the biomarker discovery process and medical decision support. It introduces study design consideration and bioanalytic concepts for generating biomedical data, followed by various data mining and information retrieval procedures such as feature selection, classification as well as statistical and clinical validation. The reviewed methods are illustrated by real examples from preclinical and clinical studies, and the application in medical decision making is discussed. This chapter is anticipated to address to those with a bioinformatics background as well as biomedical researchers who are interested in the application of computational methods in biomarker discovery and medical decision making.

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Author information

Authors and Affiliations

  1. Institute of Electrical and Biomedical Engineering, University for Health Sciences, Medical Informatics and Technology, Hall in Tirol, Austria

    M. Osl, M. Netzer & C. Baumgartner

  2. Department of Software Engineering, Upper Austria University of Applied Sciences at Hagenberg, Hagenberg, Austria

    S. Dreiseitl

Authors
  1. M. Osl
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  2. M. Netzer
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  3. S. Dreiseitl
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  4. C. Baumgartner
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Corresponding author

Correspondence to C. Baumgartner .

Editor information

Editors and Affiliations

  1. , Section for Bioinformatics, Medical University of Innsbruck, Innrain 80, Innsbruck, 6020, Austria

    Zlatko Trajanoski

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© 2012 Springer-Verlag Wien

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Osl, M., Netzer, M., Dreiseitl, S., Baumgartner, C. (2012). Applied Data Mining: From Biomarker Discovery to Decision Support Systems. In: Trajanoski, Z. (eds) Computational Medicine. Springer, Vienna. https://doi.org/10.1007/978-3-7091-0947-2_10

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