2016 Fiscal Year Final Research Report
Study on Machine Learning of Health Big Data Based on Cloud Computing
| Project/Area Number |
26350868
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Applied health science
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| Research Institution | Takasaki University of Health and Welfare |
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Principal Investigator |
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| Project Period (FY) |
2014-04-01 – 2017-03-31
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| Keywords | 健康データマイニング / 個人健康管理システム / 時系列データ解析 / クラウドコンピューティング / 機械学習 / 遅延相関分析 |
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| Outline of Final Research Achievements |
Long-term time-series data of an individual’s home blood pressure measurements were analyzed to clarify the relation with lifestyle components such as energy expenditure and supply. We found that the distribution of daily blood pressure data approached normal when the seasonal variation observed in the time-series data was adjusted. This demonstrates that adjustment is desirable for producing appropriate rules between blood pressure and lifestyle components in the healthcare data mining process. The results of healthcare data mining using the adjusted data are summarized as follows:(1)The adjustment of blood pressure data affected the rule production process and different rules were extracted with the adjustment because the blood pressure data were categorized into three classes (higher, moderate, or lower) when being used for an output (target) variable.(2)Rules extracted with the adjustment were more useful for personal healthcare than rule extracted without adjustment.
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| Free Research Field |
健康情報学
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