Risk assessment and prognosis prediction for patients with acute myocardial infarction using with data mining technique
| Project/Area Number |
22590590
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Public health/Health science
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| Research Institution | Yamaguchi University |
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Principal Investigator |
MATSUI Kunihiko 山口大学, 大学院・医学系研究科, 教授 (80314201)
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| Co-Investigator(Kenkyū-buntansha) |
KOJIMA Sunao 熊本大学, 医学部附属病院, 准教授 (50363528)
OGAWA Hisao 熊本大学, 医学薬学研究部, 教授 (50177135)
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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 |
¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2012: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2011: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2010: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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| Keywords | 急性心筋梗塞 / 予後予測 / データマイニング |
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| Research Abstract |
In this study, we used a prospective collected database of Japanese patients with acute myocardial infarction from the collaboration project of Japanese hospitals, Japan Acute Coronary Syndrome Study (JACSS).
With a data mining technique, we assessed for physicians’ decision making model including choices of invasive intervention therapies
and the patients’ outcome. Additionally, we assessed for the validity of our model. In our study results for the patients with acute myocardial infarction, the effectiveness of the invasive intervention therapy was largest for the patients with intermediate risk assessed by our prediction model.
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Report
(4 results)
Research Products
(6 results)
