Ejima Keisuke 江島啓介

Researcher Number	70730240
Other IDs	https://orcid.org/0000-0002-1185-3987
Affiliation (based on the past Project Information) *help	2020 – 2022: 東京大学, 大学院医学系研究科(医学部), 客員研究員 2018 – 2019: 東京大学, 生産技術研究所, 国際協力研究員
Review Section/Research Field	Principal Investigator Basic Section 62010:Life, health and medical informatics-related
Keywords	Principal Investigator 生活習慣病 / 骨折 / 骨密度 / 統計モデル / 生存解析 / 肥満 / 疫学

Research Projects
(1 results)
Research Products
(8 results)

Exploring association between weight trajectory and lifestyle diseases with artificial intelligence in post-menopausal womenPrincipal Investigator
- Principal Investigator
  
  Ejima Keisuke
- Project Period (FY)
  2018 – 2022
- Research Category
  
  Grant-in-Aid for Early-Career Scientists
- Review Section
  
  Basic Section 62010:Life, health and medical informatics-related
- Research Institution
  The University of Tokyo

All 2023 2021 2020 2019 2018

All Journal Article Presentation

[Journal Article] Bias in nutrition-health associations is not eliminated by excluding extreme reporters in empirical or simulation studies2023
- Author(s)
  Yamamoto Nao、Ejima Keisuke、Zoh Roger S、Brown Andrew W
- Journal Title
  
  eLife
  
  Volume: 12
- DOI
  10.7554/elife.83616
- Peer Reviewed / Open Access / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-18K18146
[Journal Article] Empirical vs theoretical power and type-I error (‘false positive’) rates estimated from real murine aging research data2021
- Author(s)
  16.Alfaras I†, Ejima K†, Teixeira CVL, Germanio CD, Sarah J. Mitchell SJ, Hamilton S, Ferrucci L, Price NL, Allison DB, Bernier M, de Cabo R
- Journal Title
  
  Cell Reports
  
  Volume: 36 Issue: 7 Pages: 109560-109560
- DOI
  10.1016/j.celrep.2021.109560
- Peer Reviewed / Open Access / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-18K18146
[Journal Article] Associations of breastfeeding or formula feeding with infant anthropometry and body composition at 6 months2020
- Author(s)
  Tahir Muna J.、Ejima Keisuke、Li Peng、Demerath Ellen W.、Allison David B.、Fields David A.
- Journal Title
  
  Maternal & Child Nutrition
  
  Volume: 17 Issue: 2
- DOI
  10.1111/mcn.13105
- Peer Reviewed / Open Access / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-18K18146
[Journal Article] Murine genetic models of obesity: type I error rates and the power of commonly used analyses as assessed by plasmode-based simulation2020
- Author(s)
  Ejima Keisuke、Brown Andrew W.、Smith Daniel L.、Beyaztas Ufuk、Allison David B.
- Journal Title
  
  International Journal of Obesity
  
  Volume: - Issue: 6 Pages: 1440-1449
- DOI
  10.1038/s41366-020-0554-2
- Peer Reviewed / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-18K18146
[Journal Article] Does exclusion of extreme reporters of energy intake (the “Goldberg cutoffs”) reliably reduce or eliminate bias in nutrition studies? Analysis with illustrative associations of energy intake with health outcomes2019
- Author(s)
  Ejima Keisuke、Brown Andrew W、Schoeller Dale A、Heymsfield Steven B、Nelson Erik J、Allison David B
- Journal Title
  
  The American Journal of Clinical Nutrition
  
  Volume: 110 Issue: 5 Pages: 1231-1239
- DOI
  10.1093/ajcn/nqz198
- Peer Reviewed / Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-18K18146
[Presentation] Assessment of Type I Error Rates and Power of Common Analysis Methods in Murine Obesity-Related Study: ‘Plasmode-Based’ Simulation2019
- Author(s)
  Keisuke Ejima
- Organizer
  ASN Scientific Sessions and Annual Meeting
- Data Source
  KAKENHI-PROJECT-18K18146
[Presentation] Postmenopausal Longitudinal Bone Mineral Density (BMD) Trajectory Improves Prediction Accuracy ofFracture Risk2019
- Author(s)
  Keisuke Ejima
- Organizer
  The International Congress on Industrial and Applied Mathematics
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-18K18146
[Presentation] Does Exclusion of Extreme Reporters of Energy Intake Make Results Less Biased in Nutrition Studies?2018
- Author(s)
  Keisuke Ejima
- Organizer
  Obesityweek
- Int'l Joint Research
- Data Source
  KAKENHI-PROJECT-18K18146

Ejima Keisuke 江島 啓介

Research Projects

Research Products

Exploring association between weight trajectory and lifestyle diseases with artificial intelligence in post-menopausal womenPrincipal Investigator

Principal Investigator

Project Period (FY)

Research Category

Review Section

Research Institution

[Journal Article] Bias in nutrition-health associations is not eliminated by excluding extreme reporters in empirical or simulation studies2023

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Empirical vs theoretical power and type-I error (‘false positive’) rates estimated from real murine aging research data2021

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Associations of breastfeeding or formula feeding with infant anthropometry and body composition at 6 months2020

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Murine genetic models of obesity: type I error rates and the power of commonly used analyses as assessed by plasmode-based simulation2020

Author(s)

Journal Title

DOI

Data Source

[Journal Article] Does exclusion of extreme reporters of energy intake (the “Goldberg cutoffs”) reliably reduce or eliminate bias in nutrition studies? Analysis with illustrative associations of energy intake with health outcomes2019

Author(s)

Journal Title

DOI

Data Source

[Presentation] Assessment of Type I Error Rates and Power of Common Analysis Methods in Murine Obesity-Related Study: ‘Plasmode-Based’ Simulation2019

Author(s)

Organizer

Data Source

[Presentation] Postmenopausal Longitudinal Bone Mineral Density (BMD) Trajectory Improves Prediction Accuracy ofFracture Risk2019

Author(s)

Organizer

Data Source

[Presentation] Does Exclusion of Extreme Reporters of Energy Intake Make Results Less Biased in Nutrition Studies?2018

Author(s)

Organizer

Data Source

Ejima Keisuke 江島啓介