Measuring the risk of chronic kidney disease for primary prevention
|關鍵字:||數學建模;繼承式雙目標基因演算法;演化式篩選演算法;國民健康訪問調查;慢性腎臟病;Mathematical Modeling;Inheritable Bi-objective Genetic Algorithm (IBCGA);Evolutionary Screening Algorithm (ESA);National Health Interview Survey (NHIS);Chronic kidney disease (CKD)|
Nowadays, there are two million people suffering from chronic kidney disease (CKD) in Taiwan. These CKD patients have to dialysis in the rest of their life. In 2015, dialysis costs approximately forty billion NT dollars from Taiwan National Health Insurance. Hence, primary prevention of chronic kidney disease can reduce the possible risk of CKD in the future, and can save huge medical expenses. The purposes of this work were to develop a non-invasive primary prevention system, to achieve early prediction, prevention, and personalized medicine. In this work, the questionnaire data were from the Health Promotion Administration, Ministry of Health and Welfare, which related to the lifestyle and diet. There are 650 CKD patients, and 5,200 people are not confirmed patients. This work based on Evolutionary Screening Algorithm to screen effective healthy people, and an accurate model derived by using the Inheritable Bi-objective Genetic Algorithm with Support Vector Machine. The results showed that the test sensitivity is 83%. In addition, 37 informative risk factors that may increase the risk of suffering from chronic kidney disease.