Contributions to cost-effectiveness analysis with probabilistic graphical models

Supervisor: Dr. Francisco Javier Díez Vegas

Given that the resources of health care systems are always limited, the economic evaluation of medical technologies is becoming more and more
important. In this context, the purpose of our doctoral thesis is to apply artificial intelligence techniques to health economics. In the last year, we have designed and implemented the required algorithms for performing cost-effectiveness analysis with Decision Analysis Networks (DANs). This new type of probabilistic graphical model, developed by our research group, will help us to build and evaluate more complex models.