| Budget Amount *help |
¥24,700,000 (Direct Cost: ¥19,000,000、Indirect Cost: ¥5,700,000)
Fiscal Year 2020: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2019: ¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2018: ¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
Fiscal Year 2017: ¥14,170,000 (Direct Cost: ¥10,900,000、Indirect Cost: ¥3,270,000)
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| Outline of Final Research Achievements |
The secondary use of large-scale medical data is becoming more and more important. The purpose of this study was to conduct epidemiological research by analyzing the NDB. And to analyze the NDB in conjunction with other databases.
In order to conduct research using the NDB, there was a problem that the data structure was complicated. Therefore, in this study, we defined a data structure that is easy for researchers to use, developed our own system for extracting and converting research data from NDB, and conducted epidemiological research. In addition, we developed a method for analyzing the data without linking the databases by using methods such as deep learning, which has been attracting attention in recent years. In addition, we constructed an actual database with ID-connected analysis.
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