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Ordinal Evolutionary Artificial Neural Networks for Solving an Imbalanced Liver Transplantation Problem

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Book cover Hybrid Artificial Intelligent Systems (HAIS 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9648))

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Abstract

Ordinal regression considers classification problems where there exists a natural ordering among the categories. In this learning setting, thresholds models are one of the most used and successful techniques. On the other hand, liver transplantation is a widely-used treatment for patients with a terminal liver disease. This paper considers the survival time of the recipient to perform an appropriate donor-recipient matching, which is a highly imbalanced classification problem. An artificial neural network model applied to ordinal classification is used, combining evolutionary and gradient-descent algorithms to optimize its parameters, together with an ordinal over-sampling technique. The evolutionary algorithm applies a modified fitness function able to deal with the ordinal imbalanced nature of the dataset. The results show that the proposed model leads to competitive performance for this problem.

This work has been subsidized by the TIN2014-54583-C2-1-R project of the Spanish Ministerial Commission of Science and Technology (MICYT), FEDER funds and the P2011-TIC-7508 project of the “Junta de Andalucía” (Spain). The authors M. Dorado-Moreno, M. Pérez-Ortíz and M.D. Ayllón-Terán have contributed equally to the preparation of this paper.

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Authors and Affiliations

  1. Department of Computer Science and Numerical Analysis, University of Córdoba, Rabanales Campus, Albert Einstein Building, 14071, Córdoba, Spain

    Manuel Dorado-Moreno, Pedro Antonio Gutiérrez & Cesar Hervás-Martínez

  2. Department of Mathematics and Engineering, Universidad Loyola Andalucía, Córdoba, Spain

    María Pérez-Ortiz

  3. Liver Transplantation Unit, Reina Sofía Hospital, Córdoba, Spain

    María Pérez-Ortiz & María Dolores Ayllón-Terán

Authors
  1. Manuel Dorado-Moreno
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  2. María Pérez-Ortiz
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  3. María Dolores Ayllón-Terán
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  4. Pedro Antonio Gutiérrez
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  5. Cesar Hervás-Martínez
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Corresponding author

Correspondence to Manuel Dorado-Moreno .

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Editors and Affiliations

  1. Universidad Pablo de Olavide, Sevilla, Spain

    Francisco Martínez-Álvarez

  2. Universidad Pablo de Olavide, Sevilla, Spain

    Alicia Troncoso

  3. University of Salamanca, Salamanca, Spain

    Héctor Quintián

  4. University of Salamanca, Salamanca, Spain

    Emilio Corchado

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Dorado-Moreno, M., Pérez-Ortiz, M., Ayllón-Terán, M.D., Gutiérrez, P.A., Hervás-Martínez, C. (2016). Ordinal Evolutionary Artificial Neural Networks for Solving an Imbalanced Liver Transplantation Problem. In: Martínez-Álvarez, F., Troncoso, A., Quintián, H., Corchado, E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2016. Lecture Notes in Computer Science(), vol 9648. Springer, Cham. https://doi.org/10.1007/978-3-319-32034-2_38

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  • DOI: https://doi.org/10.1007/978-3-319-32034-2_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-32033-5

  • Online ISBN: 978-3-319-32034-2

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