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Construction of artificial intelligence to predict incidence of hypertension and stroke based on machine learning, verification, and practice phases.

Research Project

Project/Area Number 17K19930
Research Category

Grant-in-Aid for Challenging Research (Exploratory)

Allocation TypeMulti-year Fund
Research Field Health science and related fields
Research InstitutionTeikyo University

Principal Investigator

Ohkubo Takayoshi  帝京大学, 医学部, 教授 (60344652)

Co-Investigator(Kenkyū-buntansha) 佐藤 倫広  東北医科薬科大学, 医学部, 助教 (70717892)
Project Period (FY) 2017-06-30 – 2020-03-31
Project Status Completed (Fiscal Year 2019)
Budget Amount *help
¥6,370,000 (Direct Cost: ¥4,900,000、Indirect Cost: ¥1,470,000)
Fiscal Year 2018: ¥390,000 (Direct Cost: ¥300,000、Indirect Cost: ¥90,000)
Fiscal Year 2017: ¥5,980,000 (Direct Cost: ¥4,600,000、Indirect Cost: ¥1,380,000)
Keywords高血圧 / 機械学習 / 成人保健 / 疫学 / 人工知能
Outline of Final Research Achievements

For the prediction of hypertension incidence within the next 5 years, the artificial intelligence (AI) was developed based on annual health check-up database from JMDC Inc. We then selected the same number of participants with and without hypertension incidence by the under-sampling method, respectively. We assessed the predictive value of the AI by applying it to data from the Ohasama cohort study. Although the AI developed by the logistic regression method showed better predictive value for incident hypertension than that developed by the neural network method, adequate predictive value was not observed from these two AIs. Categorization of variables, addition of other variables, or adjusting the parameter of neural network model did not significantly enhance the predictive value of AI. We also developed the AI for the prediction of stroke. However, the stroke prediction model from the JMDC database revealed low F value when it was applied to the data from the Ohasama cohort study.

Academic Significance and Societal Importance of the Research Achievements

JMDCデータで構築した高血圧・脳卒中発症予測の人工知能を大迫研究データに適用することは困難と考えられた。これは学習と検証に用いたデータに含まれる対象者特性の相違が原因と考えられる。傾向スコアマッチングによる両データの特性を一致させる、データのスケール変換などにより大迫研究データと互換性が取れるJMDCデータの再構築をする、といった前処理に関する今後の検討の必要性を明らかにした点で、本研究は萌芽研究として一定の意義を有するものと考える。

Report

(4 results)
  • 2019 Annual Research Report   Final Research Report ( PDF )
  • 2018 Research-status Report
  • 2017 Research-status Report
  • Research Products

    (6 results)

All 2019 2018

All Journal Article (2 results) (of which Peer Reviewed: 2 results) Presentation (4 results) (of which Int'l Joint Research: 1 results)

  • [Journal Article] 大規模健診時血圧データに基づく加齢に伴う血圧推移に関する縦断解析.2019

    • Author(s)
      1.佐藤倫広, 村上任尚, 小原拓, 辰巳友佳子, 高畠恭介, 原梓, 浅山敬, 今井潤, 菊谷昌浩, 大久保孝義, 目時弘仁
    • Journal Title

      日本循環器病予防学会誌

      Volume: 54 Pages: 163-169

    • Related Report
      2019 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Age-Related Trends in Home Blood Pressure, Home Pulse Rate, and Day-to-Day Blood Pressure and Pulse Rate Variability Based on Longitudinal Cohort Data: The Ohasama Study.2019

    • Author(s)
      3.Satoh M, Metoki H, Asayama K, Murakami T, Inoue R, Tsubota-Utsugi M, Matsuda A, Hirose T, Hara A, Obara T, Kikuya M, Nomura K, Hozawa A, Imai Y, Ohkubo T
    • Journal Title

      J Am Heart Assoc.

      Volume: 8

    • Related Report
      2019 Annual Research Report
    • Peer Reviewed
  • [Presentation] AGE-RELATED TRENDS IN BLOOD PRESSUR EBASED ON LARGE-SCALE HEALTH CHECKUP DATA USING LONGITUDINAL ANALYSIS.2019

    • Author(s)
      Satoh M
    • Organizer
      29th European Meeting on Hypertension and Cardiovascular.
    • Related Report
      2019 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Defined Daily Doseと比較した日本の降圧薬処方用量 レセプトデータに基づく検討2018

    • Author(s)
      佐藤 倫広, 村上 任尚, 小原 拓, 辰巳 友佳子, 高畠 恭介, 原 梓, 浅山 敬, 今井 潤, 大久保 孝義, 目時 弘仁
    • Organizer
      第21回日本医薬品情報学会総会・学術大会 2018年6月30日 三重
    • Related Report
      2018 Research-status Report
  • [Presentation] 大規模健診時血圧データに基づく加齢に伴う健診時血圧の推移に関する検討2018

    • Author(s)
      佐藤 倫広, 村上 任尚, 小原 拓, 辰巳 友佳子, 高畠 恭介, 原 梓, 浅山 敬, 今井 潤, 大久保 孝義, 目時 弘仁
    • Organizer
      第54回日本循環器病予防学会 2018年6月28日 札幌
    • Related Report
      2018 Research-status Report
  • [Presentation] 大規模健診時血圧データに基づくリアルワールドにおける降圧治療前後の血圧状況に関する前向き検討2018

    • Author(s)
      佐藤 倫広, 村上 任尚, 小原 拓, 辰巳 友佳子, 原 梓, 浅山 敬, 今井 潤, 大久保 孝義, 目時 弘仁
    • Organizer
      第7回 日本高血圧学会臨床高血圧フォーラム 2018年5月19日 京都
    • Related Report
      2018 Research-status Report

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Published: 2017-07-21   Modified: 2021-02-19  

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