A Study Of Applying Data Mining Technology To The National Health Insurance Research Database To Analyze The Death Of Stroke Patients

• Main Authors: Li-Wen Chang, 張瓈文
• Other Authors: Ben-Chang Shia
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/10826261232688987109

碩士 === 輔仁大學 === 統計資訊學系應用統計碩士班 === 100 === Stroke has been the top three of death in Taiwan's top ten causes of death in decade. For this reason, stroke is one of attentive diseases in Taiwan. In this study, the data came from Longitudinal Health Insurance Database 2005 (LHID2005) in National Health Insurance Research Database and used data from 2005 to 2009. This study used data mining technology to establish Standard Operation Procedure of National Health Insurance Research Database and built various model such as decision tree, logistic regression, neural network, random forest and support vector machine to analyze the accuracy of models mentioned and found influential factors of death after stroke. The results showed that the random forest model is the best method to predict the death after stroke. In conclusion, we hope that the Standard Operation Procedure can provide the reference of medical research.