| Project/Area Number |
23792550
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Fundamental nursing
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| Research Institution | University of Hyogo |
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Principal Investigator |
NII Manabu 兵庫県立大学, 大学院・工学研究科, 助教 (80336833)
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| Research Collaborator |
KATADA Noriko 兵庫県立大学, 看護学部, 教授 (80152677)
KAMIIZUMI Kazuko 青森県立保健大学, 健康科学部, 教授 (10254468)
UCHINUNO Atsuko 兵庫県立大学, 看護学部, 教授 (20232861)
SAKASHITA Reiko 兵庫県立大学, 看護学部, 教授 (40221999)
TEI Keiko 青森県立保健大学, 健康科学部, 准教授 (20363723)
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| Project Period (FY) |
2011 – 2012
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| Project Status |
Completed (Fiscal Year 2012)
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| Budget Amount *help |
¥3,510,000 (Direct Cost: ¥2,700,000、Indirect Cost: ¥810,000)
Fiscal Year 2012: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2011: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
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| Keywords | 看護の質向上 / テキスト分類 / ソフトコンピューティング / 機械学習 / 看護ケア / 決定木 / 遺伝的アルゴリズム / ファジィ |
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| Research Abstract |
In order to improve the nursing-care quality, we have proposed and developed a nursing-care text classification system. Our proposed system classifies the nursing-care texts using support vector machines and visualizes the classification rules using decision trees. The proposed system can classify 50% ~ 80% of nursing-care texts into four classes correctly. We also proposed a novel feature vector definition that represents structures of nursing-care texts. Using the above mentioned definition, we can easily understand classification rules generated by decision trees.
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