A Bayesian network will update probabilities based on evidence - You can use data to learn conditional probabilities and an algorithm will update the joint prob

A Bayesian network will update probabilities based on evidence - You can use data to learn conditional probabilities and an algorithm will update the joint probability distribution. However to suggest actions or further diagnostic tests you will need decision and utility nodes. This is called an influence diagram or decision model. With these extensions you can determine the best action and value of information (test vs act). The actions are based on utilities (cost/benefit) so if you have a potential very bad outcome of an action and an alternative (eg messaging to someone) then the system will act in a rational way consistent with the utility model. I suggest you look at a package that can handle both Bayesian networks and influence diagrams, such as Hugin, Norsys or Genie. There are others but I haven't tried them.