A psycho-cognitive segmentation of organ donors in Egypt using Kohonen’s self-organizing maps

This study uses self-organizing maps (SOM) to examine the effect of various psychographic and cognitive factors on organ donation in Egypt. SOM is a machine learning method that can be used to explore patterns in large and complex datasets for linear and nonlinear patterns. The results show that major variables affecting organ donation are related to perceived benefits/risks of organ donation, organ donation knowledge, attitudes toward organ donation, and intention to donate organs. The study also shows that SOM models are capable of improving clustering quality while extracting valuable information from multidimensional data.