Multi-Objective Evolutionary Algorithm for Donor-Recipient Decision System in Liver Transplants
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- Áreas de investigación:
- Año:
- 2012
- Tipo de publicación:
- Artículo
- Palabras clave:
- Artificial Neural Networks, Generalized Radial Basis Function, Liver Transplantation, Multi-Objective Evolutionary Algorithms, Organ allocations, Rule-based System
- Autores:
-
- Cruz-Ramírez, Manuel
- Hervás-Martínez, César
- Fernández, Juan Carlos
- Briceño, Javier
- de la Mata, Manuel
- Journal:
- European Journal of Operational Research
- Volumen:
- 222
- Número:
- 2
- Páginas:
- 317-327
- Mes:
- October
- ISSN:
- 0377-2217
- BibTex:
- Nota:
- JCR (2012): 2.038 Position: 9/79 (Q1) Category: OPERATIONS RESEARCH & MANAGEMENT SCIENCE
- Abstract:
- This paper reports on a decision support system for assigning a liver from a donor to a recipient on a waiting-list that maximises the probability of belonging to the survival graft class after a year of transplant and/or minimises the probability of belonging to the non-survival graft class in a two objective framework. This is done with two models of neural networks for classification obtained from the Pareto front built by a multi-objective evolutionary algorithm –called MPENSGA2. This type of neural network is a new model of the generalized radial basis functions for obtaining optimal values in C (Correctly Classified Rate) and MS (Minimum Sensitivity) in the classifier, and is compared to other competitive classifiers. The decision support system has been proposed using, as simply as possible, those models which lead to making the correct decision about receptor choice based on efficient and impartial criteria.
- Comentarios:
- JCR (2012): 2.038 Position: 9/79 (Q1) Category: OPERATIONS RESEARCH & MANAGEMENT SCIENCE