Profiling organ donors in Egypt using intelligent modeling techniques

Purpose – This study uses intelligent modeling techniques with the purpose of examining the effect of various demographic, cognitive and psychographic factors on organ donation in Egypt. Design/methodology/approach – Two artificial neural network models (multi‐layer perceptron neural network and probabilistic neural network) are compared to two standard statistical methods (linear discriminant analysis and logistic regression). The variable sets considered are sex, age, educational level, religion, altruistic values, perceived benefits/risks of organ donation, organ donation knowledge, attitudes toward organ donation, and intention to donate organs. Findings – The results show that artificial neural networks outperform traditional statistical techniques in profiling potential organ donors due to their robustness and flexibility of modeling algorithms. Originality/value – The paper shows how it is possible to identify various dimensions of organ donation behavior by uncovering patterns in the dataset, and also shows the classification abilities of two neural network techniques.