Medicine expert system dynamic Bayesian Network and ontology based

The paper proposes an application framework to be used for medicine assisted diagnosis based on ontology and Bayesian Network (DBNO). There are two goals: (1) to separate the domain knowledge from the probabilistic information and (2) to create an intuitive user interface. The framework architecture has three layers: knowledge, uncertainty model and user interface. The contributions of the domain experts are decoupled, the ontology builder will create the domain concepts and relationships focusing on the domain knowledge only. The uncertainty model is Bayesian Network and the probabilities of the variables states are stored in a profile repository. The diagnostician will use the user interface feeded with the domain ontology and one uncertainty profile. The application was tested on a sample medicine model for the diagnose of heart disease.

► An application framework used for medicine assisted diagnosis based on ontology and Bayesian Network.
► Domain knowledge is separated from the probabilistic information.
► The framework architecture has three layers: knowledge, uncertainty model and user interface.
► The contributions of the domain experts are decoupled.
► The ontology builder user will create the domain concepts and relationships focusing on the domain knowledge only.