Modeling personalised treatments for intensive care patients using Dynamic Bayesian Networks

I plan to extend dynamic Bayesian networks to assist physicians to make personalized and non myopic treatment decisions. The research activity will be oriented towards introducing the concept of personalized dynamic Bayesian network and to exploit counterfactuals for optimal sequential decision making. The main advantages and limitations of what proposed will be investigated and discussed. As for the domain of application I will concentrate on the healthcare sector with specific reference to two complex problems, i.e„ early detection of broncopulmonary dysplasia in premature babies and prognostic evaluation of functional outcomes of patients who suffered traumatic brain injuries.