Information Usefulness To Support Dialogue Management in Healthcare

The main objective of the framework we are proposing is to help the physician obtain information about the patient's condition in order to reach the \emph{correct} diagnosis as soon as possible. In our proposal, the number of interactions between the physician and the patient is reduced to a strict minimum on the one hand and, on the other hand, it is made possible to increase the number of questions to be asked if the uncertainty about the diagnosis persists. These advantages are due to the fact that (i) we implement a reasoning component that allows us to predict a symptom from another symptom without explicitly asking the patient, (ii) we consider non-binary values for the weights associated with the symptoms, we introduce a dataset filtering process in order to choose which partition should be used with respect to some particular characteristics of the patient, and, in addition, (iv) it was added new functionality to the framework: the ability to detect further future risks of a patient already knowing his pathology. The experimental results we obtained are very encouraging