Predicting patient survival after liver transplantation using evolutionary multi-objective artificial neural networks

@article{CruzRamrez2013PredictingPS,
  title={Predicting patient survival after liver transplantation using evolutionary multi-objective artificial neural networks},
  author={Manuel Cruz-Ram{\'i}rez and C{\'e}sar Herv{\'a}s-Mart{\'i}nez and Juan Carlos Fern{\'a}ndez and Javier Brice{\~n}o and Manuel de la Mata},
  journal={Artificial intelligence in medicine},
  year={2013},
  volume={58 1},
  pages={37-49}
}
OBJECTIVE The optimal allocation of organs in liver transplantation is a problem that can be resolved using machine-learning techniques. Classical methods of allocation included the assignment of an organ to the first patient on the waiting list without taking into account the characteristics of the donor and/or recipient. In this study, characteristics of the donor, recipient and transplant organ were used to determine graft survival. We utilised a dataset of liver transplants collected by… CONTINUE READING