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International Symposium on Medical Data Analysis

ISMDA 2001: Medical Data Analysis pp 195–200Cite as

Feature Selection Algorithms Applied to Parkinson’s Disease

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2199))

Abstract

In Parkinson’s Disease an analysis of Medical Data could highlight some symptoms, which can be used as a complementary tool in an early diagnosis. This paper analyses some Filter and Wrapper Feature Selection Algorithms and combinations of them that determine some relevant features in relation to this problem. The experimentation carried out with a data set of patients allows us to determine a set of different premorbid personality traits that can be considered in the early diagnosis of Parkinsonism.

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Author information

Authors and Affiliations

  1. Ramón y Cajal Hospital, Madrid, Spain

    M. Navío

  2. Dept. of Computer Science, University of Jaén, 23071, Jaén, Spain

    J. J. Aguilera & M. J. del Jesus

  3. Dept. of Medicine, University of Granada, 18071, Granada, Spain

    R. González

  4. Dept. of Computer Science and A.I., University of Granada, 18071, Granada, Spain

    F. Herrera

  5. Institute of Neuroscience, University of Granada, 18071, Granada, Spain

    C. Iríbar

Authors
  1. M. Navío
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  2. J. J. Aguilera
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  3. M. J. del Jesus
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  4. R. González
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  5. F. Herrera
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  6. C. Iríbar
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Editor information

Editors and Affiliations

  1. Polytechnical University of Madrid Artificial Intelligence Laboratory, Medical Informatics Group, 28660, Boadilla del Monte (Madrid), Spain

    Jose Crespo  & Victor Maojo  & 

  2. Health Bioinformatics Unit, Institute of Health Carlos III, Ctra. de Majadahonda-Pozuelo Km.2, 28220, Majadahonda (Madrid), Spain

    Fernando Martin

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© 2001 Springer-Verlag Berlin Heidelberg

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Cite this paper

Navío, M., Aguilera, J.J., del Jesus, M.J., González, R., Herrera, F., Iríbar, C. (2001). Feature Selection Algorithms Applied to Parkinson’s Disease. In: Crespo, J., Maojo, V., Martin, F. (eds) Medical Data Analysis. ISMDA 2001. Lecture Notes in Computer Science, vol 2199. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45497-7_29

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  • DOI: https://doi.org/10.1007/3-540-45497-7_29

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42734-6

  • Online ISBN: 978-3-540-45497-7

  • eBook Packages: Springer Book Archive

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