Using Back-Propagation Network to Predict Proper Cyclosporine Dosage in Patients After Kidney Transplantation

• Main Authors: Tsun-Hsiung Chang, 張俊雄
• Other Authors: Yo-Ping Huang
• Format: Others
• Language: zh-TW
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/82288594317129688731

碩士 === 大同大學 === 資訊工程學系(所) === 96 === Artificial intelligence technology has been extensively used in various applications. It is also used as an auxiliary tool for medical policy decision making. The application of back-propagation network in this research builds the assortment model from the history of kidney transplant patients who took the cyclosporine. About 66.29% of patients can be correctly identified by doctor’s personal experience to differentiate the results from using cyclosporine, while 86.81% of correctness is achieved by the application of back-propagation neural network strategy. We hope the results could help the medical personnel master the effectiveness of cyclosporine and improve the drug safety, the quality of using medicine, and the survival rate of kidney transplant patients.