We present a successful application of Artificial Intelligence (AI) methodologies in the context of a network oriented virtual care service for diabetic patients management, developed within the public-funded NODDS project. Several AI methods have been exploited to implement the NODDS functionality. Temporal Abstractions and other Intelligent Data Analysis techniques are used to analyse the patient's monitoring data; the Case Based Reasoning (CBR) methodology is applied to perform the Knowledge Management task. The NODDS service is being tested through a small on field trial; the first results, though preliminary, seem to substantiate the hypothesis that the use of an AI-based risk evaluation system could present an advantage in the management of type 1 diabetic patients, leading to a more tight control of the patients' metabolic situation, in a cost-effective way.

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Decision-support System Diabetes Mellitus Insulin Therapy.