Towards a dynamic knowledge base based on ontology for clinical decision support system

Currently due to the complexity of problems, several researchs are interested in developing solutions for making decision strategies. The evolution of decision support systems (DSS) showed that there is an evolution of DSS from a classical one to an intelligent DSS or knowledge based DSS. Some of these knowledge can be generated using the Knowledge Discovery from Data process (KDD). Our research focus on clinical DSS based on KDD. KDD based DSS was developed to allow, doctors in the Intensive Care Unit, predicting and preventing nosocomial infections. The last phase of KDD process is to manage the extracted knowledge and choose the appropriate decision. Since KDD is an iterative process, results can be refined by repeating the various stages many times under the control of an expert. Thus, there is a need to preserve these knowledge, in a dynamic ontology, with the suggested solutions in order to automate decision making operation with the updated knowledge and consequently obtain a DSS totally based on KDD.