A Decision Support System Based on Clinical Symptoms of Diabetes

• Main Authors: Hung-Chieh Chen, 陳宏杰
• Other Authors: Yuh-Jiuan Tsay
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/28357236600908311974

碩士 === 國立屏東科技大學 === 資訊管理系所 === 99 === In recent years, among the top ten causes of death in Taiwan, Diabetes Mellitus is the fastest rise in mortality and also a typical metabolic abnormality of chronic disease. According to the International Diabetes Federation(IDF), each year it is about three hundred and eighty million people die with diabetes-related diseases. On an average, every ten seconds there is one patient die of diabetes-related diseases and 2 new patients who get diabetes-related diseases. In this research, by using Data Mining technology to analyze the clinical records, the system not only provides physicians diverse and comprehensive information about clinical diagnosis and treatment, but also allows to reduce the incidence of complications and improve the quality of care. In this research, based on clinical symptoms of the diabetes, it has designed and implemented a Decision Support System which includes(1) Long Term Analysis Module－to analyze and integrate previous and current personal clinical data to obtain the trend graph. The module improves the integrity and accessibility of the data；(2) Risk Factor Analysis Module－by using the association rule to analyze and compare risk factors to find out the potential complications of the disease and the factor inspects that need to be tracked. This will reduce possibility of the risk factors exceeded the standard range；(3) Drug Control Analysis Module－by using the association rule to figure out the efficient drug combinations and provide further analyses of clinical treatment records that helps physicians effectively control patient’s blood sugar through the drug treatment；(4) Complications Analysis Module－by using Self-Organizing Map and United Kingdom Prospective Diabetes Study (UKPDS) prediction model to calculate future incidence of other complications, which helps physicians focus on the relate inspects in order to reduce the possibility of other derived complications.