An organ allocation system for liver transplantation based on ordinal regression
The problem of constructing an organ allocation model via machine learning techniques is assessed. The combination of donor, recipient, and surgery characteristics helps the prediction of graft survival after transplantation. An ordinal classifier has been proved to perform well for the 4-category classification problem assessed. An extended supranational experimental design for liver transplantation allocation could be feasible considering more countries.
liver transplantation ordinal regression machine learning survival analysis support vector machines decision-making