Memetic pareto differential evolutionary neural network for donor-recipient matching in liver transplantation

Authors:
M. Cruz-Ramírez;C. Hervás-Martínez;P. A. Gutiérrez;J. Briceño;M. de la Mata
Affiliations:
Dept. of Computer Science and Numerical Analysis, University of Córdoba, Spain;Dept. of Computer Science and Numerical Analysis, University of Córdoba, Spain;Dept. of Computer Science and Numerical Analysis, University of Córdoba, Spain;Liver Transplantation Unit, Hospital Reina Sofía, Córdoba, Spain;Liver Transplantation Unit, Hospital Reina Sofía, Córdoba, Spain
Venue:
IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part II
Year:
2011

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Abstract

Donor-Recipient matching constitutes a complex scenario not easily modelable. The risk of subjectivity and the likelihood of falling into error must not be underestimated. Computational tools for decisionmaking process in liver transplantation can be useful, despite its inherent complexity. Therefore, a Multi-Objective Evolutionary Algorithm and various techniques of selection of individuals are used in this paper to obtain Artificial Neural Network models to assist in making decisions. Thus, the experts will have a mathematical value that enables them to make a right decision without deleting the principles of justice, efficiency and equity.