A neural network-based approach for predicting organ donation potential

This research proposes a potential organ donor prediction model using an artificial neural network-based approach to forecast the amount of daily incoming organ referrals and their medical suitability. The daily amount of incoming organ referrals and their medical suitability indicate organ donation potential. Predicting organ donation potential is vital for organ procurement organizations (OPOs) to improve staffing and scheduling practices. As a result, the objective of this study is to develop an accurate organ donation potential prediction model that can help the OPOs in achieving their mission to save lives. Several supervised artificial neural networks were designed, tested and compared with each other to identify best prediction accuracy. The experimental results and analyses indicate that the prediction accuracy for organ donation potential depends not only on the network type, but also on the architecture selection and the choice of inputs and time frame. The constructed neural network model shows good organ potential prediction accuracy with a R-squared value of 0.73. Hence, implementing such a model can support organ procurement organizations in their mission to save lives.