Trend Analysis of Theranostics in Big Data Derived from the National Health Insurance Research Database

• Main Authors: Han-Fang Cheng, 鄭涵方
• Other Authors: Jau-Min Wong
• Format: Others
• Language: zh-TW
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/82096879114078931539

碩士 === 國立臺灣大學 === 醫學工程學研究所 === 101 === NoSQL (Not Only SQL) database has schema-free data format and the function of sharding. Comparing the NoSQL database with the relational database, the NoSQL database is more suitable to handle the big data. The big data is sharding into small blocks which are based on shard keys to speed up queries answering. To our knowledge, there is not yet a mature and systematic approach (including retrieval and visualization) to managing the big data derived from the National Health Insurance Research Database. Therefore, our research used patient document-oriented way to average the big medical data storage and to explore the field properties of the health insurance research database. By summarizing 12 important fields as shard keys in theranostics, before executing target queries can improve search efficiency. According to our experimental results, it shows that the proposed method of data processing can indeed significantly reduce the big data query time.