Hayashi, Kenichi

写真a

Affiliation

Faculty of Science and Technology, Department of Mathematics ( Yagami )

Position

Professor
Scopus Paper Info  
Paper Count: 27 Citation Count: 473 h-index: 12

Click to view the Scopus page. The data was downloaded from Scopus API in October 18, 2026, via http://api.elsevier.com and http://www.scopus.com .

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Career 【 Display / hide 】

  • 2008.04
    -
    2009.02

    同志社大学 , 文化情報学部, 実習助手

  • 2009.04
    -
    2011.03

    日本学術振興会, 特別研究員（DC2）

  • 2010.02
    -
    2010.11

    University of California, Berkeley, Department of Statistics, Visiting Scholar

  • 2011.04
    -
    2011.09

    大阪大学, 大学院医学系研究科, 特任研究員

  • 2011.10
    -
    2015.03

    大阪大学, 大学院医学系研究科, 助教

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Academic Background 【 Display / hide 】

  • 2000.04
    -
    2004.03

    Osaka University, Department of Human Sciences

    University, Graduated

  • 2005.04
    -
    2007.03

    Osaka University, Graduate School of Engineering Science, Department of Systems Science

    Graduate School, Completed, Master's course

  • 2007.04
    -
    2011.03

    Osaka University, Graduate School of Engineering Science, Department of Systems Science

    Graduate School, Withdrawal after completion of doctoral course requirements, Doctoral course

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Academic Degrees 【 Display / hide 】

  • 博士（工学）, 大阪大学, Coursework, 2011.09

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Research Areas 【 Display / hide 】

  • Informatics / Statistical science (Biostatistics)

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Books 【 Display / hide 】

  • Rで学ぶ統計的データ解析

    林 賢一, 講談社サイエンティフィク, 2020.11,  Page： 352

  • Machine Learning: The Art and Science of Algorithms that Make Sense of Data

    竹村 彰通（監訳），田中 研太郎，小林 景，兵頭 昌，片山 翔太，山本 倫生，吉田 拓真，林 賢一，松井 秀俊，小泉 和之，永井 勇, 朝倉書店, 2017.04

    Scope: 7章

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Papers 【 Display / hide 】

  • Development of an Interpersonal Harmony-Centered Enryo-Sasshi Communication Short-Form Scale and Its Association with Headache: An Epidemiological Study in the Japanese Cultural Context

    Development of an interpersonal harmony-centered Enryo-Sasshi communication short-form scale and its association with headache: An epidemiological study in the Japanese cultural context

    日本頭痛学会誌 52 ( 3 ) 565 - 573 2026.02

    Accepted

  • Statistical inference of the Matthews correlation coefficient for multiclass classification

    Tamura J., Itaya Y., Hayashi, K., Yamamoto K.

    Journal of Applied Statistics  2026

    ISSN  02664763

    　View Summary

    Classification problems underpin critical decisions, such as predicting patient prognosis and selecting treatment strategies. Accordingly, accurate evaluation of classification models is essential, and numerous metrics have been proposed. Among them, the Matthews correlation coefficient (MCC)–also called the phi coefficient–offers a balanced assessment even under severe class imbalance. However, the growing prevalence of multiclass problems (three or more classes) has led researchers to adopt macro-averaged and micro-averaged versions of MCC without formal definitions or authoritative references. This study supplies that foundation by formally defining both extensions and detailing their statistical properties. To move beyond point estimates, we develop several methods for constructing asymptotic confidence intervals for the proposed metrics. We further extend these techniques to derive confidence intervals for paired differences, enabling rigorous comparison of competing classifiers within the same subjects. The performance of the intervals is investigated through comprehensive simulation studies and demonstrated on real-world biomedical datasets. Our framework equips practitioners with principled, readily implementable tools for statistically sound evaluation of multiclass classification performance.

  • Variable selection methods based on pseudo-observations in competing risks analysis

    Tajima, F., Hayashi, K.

    International Journal of Statistics and Probability 14 ( 2 ) 37 - 54 2025.07

    Research paper (scientific journal), Joint Work, Last author, Corresponding author, Accepted

  • Asymptotic properties of Matthews correlation coefficient

    Itaya, Y., Tamura, J., Hayashi, K., Yamamoto, K.

    Statistics in Medicine 44 ( 1-2 )  2025.01

    Research paper (scientific journal), Joint Work, Accepted,  ISSN  02776715

    　View Summary

    Evaluating classifications is crucial in statistics and machine learning, as it influences decision-making across various fields, such as patient prognosis and therapy in critical conditions. The Matthews correlation coefficient (MCC), also known as the phi coefficient, is recognized as a performance metric with high reliability, offering a balanced measurement even in the presence of class imbalances. Despite its importance, there remains a notable lack of comprehensive research on the statistical inference of MCC. This deficiency often leads to studies merely validating and comparing MCC point estimates—a practice that, while common, overlooks the statistical significance and reliability of results. Addressing this research gap, our paper introduces and evaluates several methods to construct asymptotic confidence intervals for the single MCC and the differences between MCCs in paired designs. Through simulations across various scenarios, we evaluate the finite-sample behavior of these methods and compare their performances. Furthermore, through real data analysis, we illustrate the potential utility of our findings in comparing binary classifiers, highlighting the possible contributions of our research in this field.

  • Partial areas under the curve of the cumulative distribution function as a new composite estimand for randomized clinical trials

    Taguri, M., Hayashi, K.

    Statistical Methods in Medical Research 34 ( 6 ) 1097 - 1113 2025

    Joint Work, Last author, Accepted,  ISSN  09622802

    　View Summary

    Clinical trials often face the challenge of post-randomization events, such as the initiation of rescue therapy or the premature discontinuation of randomized treatment. Such events, called “intercurrent events” (ICEs) in ICH E9(R1), may influence the estimation and interpretation of treatment effects. According to ICH E9(R1), there are five strategies for handling ICEs. This study focuses on the composite strategy, which incorporates ICEs in the outcome of interest and defines the treatment effects using composite endpoints that combine the measured continuous variables and ICEs. An advantage of this strategy is that it avoids the occurrence of missing data because they are defined as part of the outcome of interest. In this study, we propose a new composite estimand: the difference in the partial areas under the curves (pAUCs) of the cumulative distribution function. While the pAUC is closely related to the trimmed mean approach proposed by Permutt and Li, it offers the advantage of allowing pre-specification of the cutoff value for a “good” response based on clinical considerations. This ensures that the pAUC can be calculated irrespective of the proportion of ICEs. We describe the causal interpretation of our method and its relationship with two other strategies (treatment policy and hypothetical strategies) using a potential outcome framework. We present simulation results in which our method performs reasonably well compared to several existing approaches in terms of type I error, power, and the proportion of undefined test statistics.

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Papers, etc., Registered in KOARA 【 Display / hide 】

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Reviews, Commentaries, etc. 【 Display / hide 】

  • 医学のための標的学習の基礎 II：無作為化比較試験における共変量調整

    田栗 正隆, 高橋 邦彦, 小向 翔, 伊藤 ゆり, 服部 聡, 船渡川 伊久子, 篠崎 智大, 山本 倫生, 林 賢一

    計量生物学 44 ( 2 )  2024

    Article, review, commentary, editorial, etc. (scientific journal), Joint Work

  • Statistics is not alchemy

    林 賢一

    Japanese Psychological Review 61 ( 1 ) 147 - 155 2018.07

    Article, review, commentary, editorial, etc. (scientific journal), Single Work, Lead author, Corresponding author

  • 労働時間と飲酒行動

    吉田 恵子，林 賢一

    桃山学院大学経済経営論集 56 ( 1 ) 153 - 164 2014.11

    Rapid communication, short report, research note, etc. (bulletin of university, research institution), Joint Work, Last author

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Presentations 【 Display / hide 】

  • Estimation of true positive rate under nonignorable verification bias: An instrumental variable approach

    Masaki, D., Hayashi, K.

    [International presentation]  NCKU-Keio Joint Workshop for Statistics, Econometrics, Mathematics, Business Analytics and Data Science, 

    2026.10
    , 

    Poster presentation

  • Multiclass generalizations of the F-score: issues and alternatives

    Hayashi, K.

    [International presentation]  NCKU-Keio Joint Workshop for Statistics, Econometrics, Mathematics, Business Analytics and Data Science, 

    2026.10
    , 

    Oral presentation (general)

  • Introduction to adaptive index models for survival outcomes: An application to data on elderly non-cancer patients at home

    Date, K., Tsukada, K., Hayashi, K.

    [International presentation]  NCKU-Keio Joint Workshop for Statistics, Econometrics, Mathematics, Business Analytics and Data Science, 

    2026.10
    , 

    Poster presentation

  • Product-CCA: An ordering-robust canonical correlation analysis procedure without efficiency loss

    Hayashi, K., Hung, H.

    [International presentation]  The 9th International Conference on Econometrics and Statistics (EcoSta 2026), 

    2026.08
    , 

    Oral presentation (invited, special)

  • Theoretical foundations and asymptotic confidence intervals for Matthews Correlation Coefficients in multiclass classification

    Tamura, J., Yamamoto, K., Hayashi, K.

    [International presentation]  The 9th International Conference on Econometrics and Statistics (EcoSta 2026), 

    2026.08
    , 

    Oral presentation (invited, special)

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Research Projects of Competitive Funds, etc. 【 Display / hide 】

  • Integrated understanding of statistical analysis for imbalanced data and its advanced application to survival analysis

    2023.04
    -
    2027.03

    MEXT,JSPS, Grant-in-Aid for Scientific Research, Grant-in-Aid for Scientific Research (C), Principal investigator

  • Developments and applications of statistical prediction method

    2018.04
    -
    2023.03

    MEXT,JSPS, Grant-in-Aid for Scientific Research, Grant-in-Aid for Scientific Research (B), Coinvestigator(s)

  • Development of statistical models for data containing heterogeneous subgroups using statistical learning theory and its application to clinical medicine

    2018.04
    -
    2022.03

    MEXT,JSPS, Grant-in-Aid for Scientific Research, Grant-in-Aid for Scientific Research (C), Principal investigator

  • A study on exploratory identification of responsive subgroups in complex survival event data

    2015.04
    -
    2018.03

    MEXT,JSPS, Grant-in-Aid for Scientific Research, Grant-in-Aid for Young Scientists (B), Principal investigator

  • Development of C-index-based survival tree and its application to biomedical research

    2012.04
    -
    2015.03

    MEXT,JSPS, Grant-in-Aid for Scientific Research, Grant-in-Aid for Young Scientists (B), Principal investigator

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Awards 【 Display / hide 】

  • 最優秀賞（ポスター部門）

    岡田和也，林賢一, 2024.01,  2023年度スポーツデータサイエンスコンペティション事務局, 2023年度スポーツデータサイエンスコンペティション

    Type of Award： Award from Japanese society, conference, symposium, etc.

    　View Description

    岡田和也（理工学部数理科学科，筆頭著者）との共同研究

  • 若手優秀発表賞

    2021.05, 日本計量生物学会

    Type of Award： Award from Japanese society, conference, symposium, etc.

    　View Description

    2021年度計量生物学会年会 若手優秀発表賞（正会員の部）

  • 最優秀賞

    奥富航，林賢一, 2018.01, 第7回スポーツデータ解析コンペティション審査会, 第7回スポーツデータ解析コンペティション

    Type of Award： Award from Japanese society, conference, symposium, etc.

    　View Description

    奥富航（理工学部数理科学科，筆頭著者）との共同研究

  • 論文賞

    2017.12, 日本分類学会, 日本分類学会

    Type of Award： Award from Japanese society, conference, symposium, etc.

  • 論文賞

    2015.05, 日本計算機統計学会, 日本計算機統計学会

    Type of Award： Award from Japanese society, conference, symposium, etc.

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Courses Taught 【 Display / hide 】

  • DOCTORAL RESEARCH ON MATHEMATICAL AND PHYSICAL SCIENCES

    2026

  • MATHEMATICAL SCIENCES PRACTICAL RESEARCH ACTIVITY C

    2026

  • MATHEMATICS 1A

    2026

  • MATHEMATICAL SCIENCES PRACTICAL RESEARCH ACTIVITY D

    2026

  • GRADUATE RESEARCH ON MATHEMATICAL AND PHYSICAL SCIENCES 2

    2026

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Courses Previously Taught 【 Display / hide 】

  • 行動計量科学特講I

    The University of Osaka

    2026.09
    , 

    Spring Semester, Lecture, Outside own faculty (within Keio)

  • 経営工学特別講義・情報工学特別講義

    Tokyo University of Science

    2021.10
    , 

    Autumn Semester, Postgraduate

  • 理科演習

    慶應女子高等学校

    2017.01
    , 

    Autumn Semester, Other, 1h

  • 疫学総論

    Osaka University

    2016.05
    , 

    Spring Semester, Postgraduate, 1h

  • 数理科学講演会

    慶應義塾湘南藤沢高等部

    2016.03
    , 

    Autumn Semester, Other

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Memberships in Academic Societies 【 Display / hide 】

  • 日本分類学会, 

    2017.10
    -
    Present

  • 日本計量生物学会, 

    2014.04
    -
    Present

  • International Biometric Society, 

    2014.04
    -
    Present

  • 日本疫学会, 

    2014.04
    -
    2026.11

  • 日本計算機統計学会, 

    2013.04
    -
    Present

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Committee Experiences 【 Display / hide 】

  • 2021.04
    -
    2022.02

    NEDO先導研究プログラム外部有識者

  • 2021
    -
    2021.11

    副実行委員長（第35回シンポジウム）, 日本計算機統計学会

  • 2020
    -
    2021.03

    副実行委員長（2021年度年会）, 日本数学会

  • 2018
    -
    Present

    Associate Editor, Japanese Journal of Statistics and Data Science

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