Estimation of cardiovascular patient risk with a Bayesian network

Cardiovascular decision-making support experiences increasing research interest of scientists. Ongoing collaborations between clinicians and computer scientists are looking at the application of data mining techniques to the area of individual patient diagnosis, based on clinical records. An investigation of a Bayesian network learnt according to a generated decision tree with cardiovascular data for estimation of patient risk in cardiovascular domains is presented. Promising experimental results are also provided.