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 decision-making 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.
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Cruz-Ramírez, M., Hervás-Martínez, C., Gutiérrez, P.A., Briceño, J., de la Mata, M. (2011). Memetic Pareto Differential Evolutionary Neural Network for Donor-Recipient Matching in Liver Transplantation. In: Cabestany, J., Rojas, I., Joya, G. (eds) Advances in Computational Intelligence. IWANN 2011. Lecture Notes in Computer Science, vol 6692. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21498-1_17
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DOI: https://doi.org/10.1007/978-3-642-21498-1_17
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