A knowledge-based risk advisor model for chronic complications of diabetes

Diabetes as an unprecedented epidemic is spreading all around the world. While one in every seven health care dollars in USA is spent on diabetes, 60% of direct costs and almost 80-90% of indirect costs of that are related to diabetic complications. The ultimate aim of this study is to develop a rule-based model for advising the risk of chronic diabetic complications. An extensive literature review has been carried out to gather actual knowledge about diabetic complications and their related predisposing factors. NViv08 is used to organize and categorize the acquired knowledge. A rule-based decision support model is constructed from the obtained knowledge. CLIPS is used to represent and implement the rules and build a knowledge based decision support system.