Medicine expert system dynamic Bayesian Network and ontology based

Authors:
Octavian Arsene;Ioan Dumitrache;Ioana Mihu
Affiliations:
Laboratory of Intelligent Systems, "Politehnica" University of Bucharest, SPl. Independentei 313, 060042 Bucharest, Romania;Laboratory of Intelligent Systems, "Politehnica" University of Bucharest, SPl. Independentei 313, 060042 Bucharest, Romania;Laboratory of Intelligent Systems, "Politehnica" University of Bucharest, SPl. Independentei 313, 060042 Bucharest, Romania
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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Abstract

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.