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Impact of time series discretization on intensive care burn unit survival classification

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Abstract

In the preprocessing step of a knowledge discovery process, the method of discretization selected can have a remarkable impact on the performance and accuracy of classification algorithms. In this article, we analyze and compare expert discretization and automatic discretization algorithms. In particular, we study their impact to predict the survival of patients in the context of intensive care burn units. We focus on the quality of different discretizations algorithm analyzing the number of intervals generated, the amount of patterns produced and the classification performance in a specific clinical problem. Our results show that the many algorithms underperform expert discretization and that it is necessary to take into account the correlation among continuous features to obtain the best accuracy.

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Acknowledgements

This work was partially funded by the Spanish Ministry of Economy and Competitiveness under project TIN2013-45491-R, European Fund for Regional Development (EFRD),and Instituto de Salud Carlos III (Ref: FIS PI 12/2898).

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Authors and Affiliations

  1. Computer Science Faculty, University of Murcia, Murcia, Spain

    Isidoro J. Casanova, Manuel Campos & Jose M. Juarez

  2. University Hospital of Getafe, Getafe, Spain

    Antonio Fernandez-Fernandez-Arroyo & Jose A. Lorente

  3. European University of Madrid, Madrid, Spain

    Antonio Fernandez-Fernandez-Arroyo & Jose A. Lorente

  4. CIBER Enfermedades Respiratorias, Madrid, Spain

    Antonio Fernandez-Fernandez-Arroyo & Jose A. Lorente

Authors
  1. Isidoro J. Casanova
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  2. Manuel Campos
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  3. Jose M. Juarez
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  4. Antonio Fernandez-Fernandez-Arroyo
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  5. Jose A. Lorente
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Correspondence to Manuel Campos.

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Casanova, I.J., Campos, M., Juarez, J.M. et al. Impact of time series discretization on intensive care burn unit survival classification. Prog Artif Intell 7, 41–53 (2018). https://doi.org/10.1007/s13748-017-0130-8

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