Functional data analysis for medical data and its application
| Project/Area Number |
22700298
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
Statistical science
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| Research Institution | Kurume University |
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Principal Investigator |
ARAKI Yuko 久留米大学, バイオ統計センター, 助教 (80403913)
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| Project Period (FY) |
2010 – 2012
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| Project Status |
Completed (Fiscal Year 2012)
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| Budget Amount *help |
¥3,120,000 (Direct Cost: ¥2,400,000、Indirect Cost: ¥720,000)
Fiscal Year 2012: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2011: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2010: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
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| Keywords | 医薬生物 / ゲノム統計解析 / 関数化データ解析 / 関数データ解析 / 情報量基準 / 高次元医学データ / 基底展開法 / 正則化法 / 変数選択 / スパース性 / 高次元データ / 情報量規準 / 判別モデル / 統計的モデリング / 生物統計 / 次元縮小 / モデル選択 / 判別 |
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| Research Abstract |
To extract valuable information from medical data which has a lots of observational points result in high dimensional data with complex structure, we developed statistical methods and applied them to the analysis of medical data. We proposed functional data analytic approach for dimension reduction of high dimensional data such as medical imaging data, brain waves or shape data. We further proposed classification model for high dimensional data and its evaluation methods. We also developed an efficient nonlinear model selection method based on information criterion. The proposed methods were applied to life science problems.
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Report
(4 results)
Research Products
(39 results)
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[Journal Article] 低置胎盤の術中出血量に影響を及ぼす因子についての検討.2011
Author(s)
蔵本昭孝,堀大蔵,井上茂,堀之内崇士,品川貴章,上妻友隆,下村卓也,河田高伸,林龍之介,嘉村敏治,山下拓人,荒木由布子,角間辰之.
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Journal Title
日本周産期・新生児医学会雑誌
Volume: 47(4)
Pages: 873-877
NAID
Related Report
Peer Reviewed
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