Identify High Risk Group of Diabetes Mellitus Using Mathematical Modeling

• Main Authors: Cai,Yu-Shan, 蔡毓珊
• Other Authors: Ho,Shinn-Ying
• Format: Others
• Language: zh-TW
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/d6cj25

碩士 === 國立交通大學 === 生物資訊及系統生物研究所 === 105 === Background: The Prevention of primary Diabetes always screens high risk group of Diabetes through the non-invasive of inspection. Therefore, I look forward to comprehend the lifestyle in this research and pick an impact factor which is more important to predict the Diabetes mellitus. So it will achieve individual primary prevention of diabetes. Methods: It will use the Databank of National Health Interview Survey Database to research the Healthy Eating Style of Taiwanese and Diabetes mellitus. After data processing, there has 886 samples suffer from a Diabetes, 2595 unverified healthy samples. To screen useful healthy samples by using Evolutionary screening algorithm(ESA) and choose an importance of impact factor. At last use the Support Vector Machine(SVM) to build the Mathematical Modeling. Results: Totally choosing 30 impact factor after the feature selection, including household heredity factors (Diabetes, hyperlipidemia, heart disease),taking blood pressure lowering drugs, vision problems, dental condition, medical condition, blood pressure status, blood lipid status, Drinking, sitting time, diet status, psychological status, gender, working condition. Also use this Mathematical Modeling to predict it, and it increased by 20% to 91% in the sensitivity of testing data. Conclusions: The results of the study show that the health samples will enhance the ability of the mathematical model to predict the accuracy of diabetes. Finally found 30 important factors to predict the Diabetes mellitus. And it also can be used to prevent the Primary of Diabetes mellitus.