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International Conference on Artificial Intelligence and Soft Computing

ICAISC 2012: Artificial Intelligence and Soft Computing pp 387–393Cite as

Competing Risks and Survival Tree Ensemble

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7267))

Abstract

In the paper the ensemble of dipolar trees for analysis of competing risks is proposed. The tool is build on the base of the learning sets, which contain the data from clinical studies following patients response for a given treatment. In case of competing risks many types of response are investigated. The proposed method is able to cope with incomplete (censored) observations and as a result, for a given set of covariates and a type of event, returns the aggregated cumulative incidence function.

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References

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Author information

Authors and Affiliations

  1. Faculty of Computer Science, Bialystok University of Technology, Wiejska 45a, 15-351, Białystok, Poland

    Małgorzata Krętowska

Authors
  1. Małgorzata Krętowska
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Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Armii Krajowej 36, 42-200, Częstochowa, Poland

    Leszek Rutkowski , Marcin Korytkowski  & Rafał Scherer ,  & 

  2. AGH University of Science and Technology, Mickiewicza 30, 30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  3. Department of Electrical Engineering and Computer Sciences, Computer Science Division, University of California Berkeley, 94720-1776, Berkeley, CA, USA

    Lotfi A. Zadeh

  4. Computational Intelligence Laboratory, Electrical and Computer Engineering, University of Louisville, 405 Lutz Hall, 40292, Louisville, KY, USA

    Jacek M. Zurada

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© 2012 Springer-Verlag Berlin Heidelberg

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Krętowska, M. (2012). Competing Risks and Survival Tree Ensemble. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2012. Lecture Notes in Computer Science(), vol 7267. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29347-4_45

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  • DOI: https://doi.org/10.1007/978-3-642-29347-4_45

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29346-7

  • Online ISBN: 978-3-642-29347-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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