Intelligent Insulin Dosing System

We will develop an intelligent decision support system for optimal insulin dosing for Type l Diabetmanagement. The hypothesis used in this study is that case-based reasoning (CBR) methodology in theintelligence (AI) can learn an individual's unique response to diet and exercise and provide a comprits decision in each case; and that the self-organizing fuzzy neural network controller (SOFNNC) canand its predictive control capability to determine the correct insulin dose input for maintaining thwithin an optimal range. In Phase I, as a proof-of-concept, a prototype system will be developed andto changes in diet and exercise, for a group of well-selected and well- controlled patients. The intsystem should enhance the ability of patients to balance diet, activity, and insulin. This will tranlower costs.