2021 Fiscal Year Final Research Report
Meta-analyses of artificial intelligence for promoting evidence-based medicine of non-communicable diseases
Project/Area Number |
19K12840
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Research Category |
Grant-in-Aid for Scientific Research (C)
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Allocation Type | Multi-year Fund |
Section | 一般 |
Review Section |
Basic Section 90130:Medical systems-related
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Research Institution | Niigata University |
Principal Investigator |
Kodama Satoru 新潟大学, 医歯学総合研究科, 特任准教授 (50638781)
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Co-Investigator(Kenkyū-buntansha) |
加藤 公則 新潟大学, 医歯学総合研究科, 特任教授 (00303165)
藤原 和哉 新潟大学, 医歯学総合研究科, 特任准教授 (10779341)
渡邊 賢一 新潟大学, 医歯学総合研究科, 客員研究員 (70175090)
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Project Period (FY) |
2019-04-01 – 2022-03-31
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Keywords | 人工知能 / 糖尿病 / メタ解析 |
Outline of Final Research Achievements |
Evidence for usefulness of artificial intelligence (AI) in primary prevention of non-communicable diseases has not been established. This project aimed to assess the ability of AI to predict the onset of non-communicable diseases, focusing on type 2 diabetes mellitus (T2D) and hypoglycemia, a major barrier of treating diabetes, using a meta-analytic technique. The results of meta-analysis were interpret as meaning that the ability of current machine learning was acceptable for clinicians to discriminate individuals at high risk of T2D but insufficient for individuals to recognize their risk of T2D and that it is sufficient as a tool for patients with diabetes to prepare for their impeding hypoglycemia. The study is the first step to apply the AIs to clinical practice of non-communicable diseases, especially identifying individuals which were at high risk and thus require strict managements for primary prevention.
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Free Research Field |
医療情報学
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Academic Significance and Societal Importance of the Research Achievements |
予後予測に必須であるが、原理・解釈が難しく敬遠されがちなhierarchical summary receiver operating characteristicモデルを用いたメタ解析を大々的に行った研究プロジェクトである。人工知能の糖尿病、低血糖予測能力を評価した本研究は、社会的要請の高いAIの糖尿病診療にとって極めて重要な布石であり、今後、他の生活習慣病への拡張も期待大である。
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