A Study of Applying Artificial Intelligence to Hyperuricemia

• Main Authors: Yu-Ho Yang, 楊祐龢
• Other Authors: 張俊郎
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/zs22bu

碩士 === 國立虎尾科技大學 === 工業工程與管理研究所 === 98 === Hyperuricemia is nowadays considered one of the important complications to diagnose chronic or regressive illnesses. According to the public nutrition investigation conducted by the Health Department in Taiwan, one out of four male adults and one out of six female adults developed hyperuricemia and the population with uric acid above the normal range reached 5 millions. Hyperuricemia is an essential condition and effective bio-chemical data for testing early stage of gout. Over 97% of gout patients also develop hyperuricemia; however, not all patients with hyperuricemia will necessarily develop gout. Patients with severe hyperuricemia symptoms will very likely develop other serious diseases such as gout, and/or kidney function decline (or renal failure). Without proper treatment, multiple complications might develop thus leading to the onsets of other major diseases and eventually put patients’ lives in jeopardy. In this study, artificial intelligence methodologies were utilized, using the data base of a case medical institution as the subject, we evaluated and compared the three different models using BPN network, decision tree, and decision tree with BPN networks respectively to construct a predictive model to help determine the causes of hyperuricemia. The results show that using decision tree combining with artificial neural network model has more optimal analytical performance in the classification prediction with a mean accuracy at 90.28%, indicating that the combination model has better explanatory ability to the causes of hyperuricemia. This study also attempted to explore the association and classification rules among data through artificial intelligence methods to help provide physicians the reference in clinical diagnosis as well as to promote health knowledge on hyperuricemia, and to increase public awareness of their own health conditions, hoping for them to effectively manage their changes of life styles and taking routine examinations for hyperuricemia. Early diagnoses and early treatments can then be provided to people at risk so to reduce the onset of hyperuricemia. The implementation of the system can provide more practical benefits to prevent chronic diseases from developing and to enhance the quality of life.