2022 Fiscal Year Final Research Report
Comprehensive research on statistical methodologies and their applications for development of personalized medicine
| Project/Area Number |
16H06299
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| Research Category |
Grant-in-Aid for Scientific Research (S)
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| Allocation Type | Single-year Grants |
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| Research Field |
Statistical science
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| Research Institution | Nagoya University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
山田 誠 京都大学, 情報学研究科, 准教授 (00581323)
角田 達彦 東京大学, 大学院理学系研究科(理学部), 教授 (10273468)
山下 智志 統計数理研究所, データ科学研究系, 教授 (50244108)
服部 聡 大阪大学, 医学系研究科, 教授 (50425154)
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| Project Period (FY) |
2016-05-31 – 2021-03-31
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| Keywords | 統計科学 / 生物統計学 / 機械学習 / 個別化医療 / 臨床研究 / 研究デザイン / データ解析 |
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| Outline of Final Research Achievements |
We have developed statistical and machine learning methods and tools for the clinical development of personalized medicine and conducted many case studies in a wide range of disease fields. By comprehensively covering the main phases for developing personalized medicine, including the development and evaluation of diagnostic markers, evaluation of the efficacy of treatments based on diagnostic markers, integration of evidence for personalized medicine based on diagnostic markers, and marker-based decision-making in selecting treatment in medical practice, we have developed statistical and machine learning methodologies that are truly useful for clinical development of personalized medicine.
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| Free Research Field |
生物統計学
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| Academic Significance and Societal Importance of the Research Achievements |
個別化医療の臨床開発のための統計・機械学習の方法論の構築は、統計科学・情報学の発展につながり、健康医療領域での統計科学・情報学の応用研究の発展にもつながる。一方、個別化医療の開発に役立つ統計・機械学習の方法論を構築することで、限られた医療資源を用いた個別化医療開発の効率性、成功確率の向上につながり、個別化医療の推進に直接的に貢献する。
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