We present a knowledge management and decision support methodology for insulin dependent diabetes mellitus (IDDM) patients care. Such methodology exploits the integration of case based reasoning (CBR) and rule based reasoning (RBR), with the aim of helping physicians during therapy planning, by overcoming the intrinsic limitations shown by the independent application of the two reasoning paradigms. RBR provides suggestions on the basis of a situation detection mechanism that relies on formalized prior knowledge; CBR is used to specialize and dynamically adapt the rules on the basis of the patient's characteristics and of the accumulated experience. When the case library is not representative of the overall population, only RBR is applied to define a therapy for the input situation, which can then be retained, enriching the case library competence. The paper reports the first evaluation results, obtained both on simulated examples and on real patients. This work was developed within the EU funded telematic management of insulin dependent diabetes mellitus (T-IDDM) project, and is fully integrated in its web-based architecture.
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