Application of Data Mining Techniques on the Prediction of Hypertension: Using National Health Insurance Inpatient Database
碩士 === 國立臺北大學 === 企業管理學系 === 103 === According to the research of Ministry of Health and Welfare, in Taiwan, there are fourteen people per day die of hypertension. This study is about discovering those risk factors of hypertensive disease by applying data mining technique. Also, this approach provid...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2015
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| Online Access: | http://ndltd.ncl.edu.tw/handle/282x9e |
| Summary: | 碩士 === 國立臺北大學 === 企業管理學系 === 103 === According to the research of Ministry of Health and Welfare, in Taiwan, there are fourteen people per day die of hypertension. This study is about discovering those risk factors of hypertensive disease by applying data mining technique. Also, this approach provides a method to improve the accuracy of diagnosis and help to control high blood pressure. Data mining is a part of the knowledge discovery which is in order to select the appropriate data and some useful knowledge from the data processing. National Health Insurance Research Database contains many different data which is called “Big Data”, so it is suitable to analyze by applying data mining techniques.
This study use the data from National Health Insurance Research Database by two approaches including decision tree and association rule. The results show that the data can be divided into three categories of complications from hypertension, including the complications which have been confirmed, diseases of old age and hypertension during pregnancy.
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