Updated on 2026/03/03

写真a

 
TANAKA Noriko
 
Organization
Research Facility Attached to the School of Medicine Department of Biomolecular Science Professor
Title
Professor

Research Interests

  • Genetic Epidemiology

  • Genetic Polymorphism

  • Biometry

  • 臨床生命情報学

  • Statistical Genetics

  • Statistical Modeling

  • 生物統計学

  • Survival Analysis

  • Measurement Error/ misclassification

  • Epidemiology

  • Competing risk

  • Clinical Bioinformatics

  • Biostatistics

Research Areas

  • Life Science / Genetics  / 計量遺伝学

  • Informatics / Statistical science  / Biostatistics

  • Informatics / Statistical science

Education

  • The University of Tokyo   Graduate School of Medicine   Dept.Biostatistics

    - 2004.3

      More details

    Country: Japan

  • The University of Tokyo

    - 1999.3

      More details

    Country: Japan

Research History

  • Fukushima Medical University   School of Medicine Institute of Biomedical Sciences Dept. Biometry and Genetics   Research Professor

    2024.10 - Now

  • Kyoto University   Graduate School of Biostudies

    2023.10 - 2024.9

  • National Center for Global Health and Medicine   Research Institute, Genome Medical Science Project - toyama   Project Scientist

    2023.9 - 2024.3

  • Tokyo Metropolitan Geriatric Hospital and Institute of Gerontology   Dept. Health Data Science Research   Department Director

    2019.4 - 2023.8

  • Fukushima Medical University   Specially Appointed Associate Professor

    2018.9 - 2024.9

  • Waseda University   School of Advanced Science and Engineering   Part-time Lecturer

    2017.4 - Now

  • Tokyo Medical and Dental University   Part-time Lecturer

    2015.4 - 2024.3

  • National Center for Global Health and Medicine   Biostatistics Section, Clinical Research Center   Section Chief

    2012.8 - 2019.8

  • National Surgical Adjuvant Breast and Bowl Project/University of Pittsburgh   Pathology Lab/ Department of Biostatistics   Biostaitstics/Bioinformatics Specialist   Adjunct Research Assistant Professor

    2010.12 - 2012.7

  • Dana Farber Research Institute, Harvard University   Dept. Medical Oncology   Bioinformatics analyst

    2009.9 - 2010.9

  • Grad School of Public Health, Harvard University   Dept.Biostatistics   Visiting Scientist

    2007.9

  • RIKEN   Research Scientist

    2007.4 - 2007.8

  • Grad School of Medicin, the University of Tokyo   Clinical Bioinformatics Research Unit   Project Assistant Professor

    2004.4 - 2007.3

▼display all

Professional Memberships

  • 日本人類遺伝学会

    2024.9 - Now

  • THE JAPAN STATISTICAL SOCIETY

  • 日本疫学会

  • International society for clinical biostatistics

  • American statistical association

  • 計量生物学会

▼display all

Papers

▼display all

Awards

  • Outstanding poster presentation

    2015  

  • Outstanding poster presentation

    2014  

  • Post-doctoral Fellowship for study abroad

    2006.4  

Research Projects

  • Survival analysis for estimating the effect of age and aging

    Grant number:25K15023  2025.4 - 2028.3

    Grant-in-Aid for Scientific Research (C)

      More details

    Grant amount:\4680000 ( Direct Cost: \3600000 、 Indirect Cost:\1080000 )

  • Competing risks analysis with misclassified outcome and sensitivity analysis

    Grant number:18K10073  2018.4 - 2023.3

    Grant-in-Aid for Scientific Research (C)

    Mieno Makiko

      More details

    Grant amount:\4290000 ( Direct Cost: \3300000 、 Indirect Cost:\990000 )

    In clinical and epidemiological studies, when analyzing the original cause of death on the death certificates, large bias in the estimated risk factors should be found if there is a large misclassification between the recorded causes of death. In this study, we investigated risk estimation methods and sensitivity analysis methods using a method that takes into account the characteristics of misclassification of causes of death. It was suggested that misclassification may have a particularly large impact on the conclusions in large-scale epidemiological studies, and that it is necessary to carefully consider factors that affect the accuracy of outcome classification when estimating risks.