慶應義塾研究者情報データベース

研究分野 【 表示 ／ 非表示 】

研究分野 【 表示 ／ 非表示 】

• 情報通信 / 統計科学

著書 【 表示 ／ 非表示 】

著書 【 表示 ／ 非表示 】

• 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年11月,  ページ数： 352

• 機械学習 ─データを読み解くアルゴリズムの技法─

  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年04月

  担当範囲: 7章

論文 【 表示 ／ 非表示 】

論文 【 表示 ／ 非表示 】

• Asymptotic Properties of Matthews Correlation Coefficient

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

  Statistics in Medicine 44 （ 1-2 ）  2025年01月

  ISSN  02776715

  　概要を見る

  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.

  • Access to Document (DOI)

• A new integrated discrimination improvement index via odds

  Hayashi K., Eguchi S.

  Statistical Papers 65 （ 8 ） 4971 - 4990 2024年10月

  ISSN  09325026

  　概要を見る

  Consider adding new covariates to an established binary regression model to improve prediction performance. Although difference in the area under the ROC curve (delta AUC) is typically used to evaluate the degree of improvement in such situations, its power is not high due to being a rank-based statistic. As an alternative to delta AUC, integrated discrimination improvement (IDI) has been proposed by Pencina et al. (2008). However, several papers have pointed out that IDI erroneously detects meaningless improvement. In the present study, we propose a novel index for prediction improvement having Fisher consistency, implying that it overcomes the problems in both delta AUC and IDI. Furthermore, our proposed index also has an advantage that the index we proposed in our previous study (Hayashi and Eguchi 2019) lacked: it does not require any hyperparameters or complicated transformations that would make interpretation difficult.

  • Access to Document (DOI)

• Model Selection with Missing Data Embedded in Missing-at-Random Data

  Takai K., Hayashi K.

  Stats （Stats）  6 （ 2 ） 495 - 505 2023年06月

  共著, 査読有り

  　概要を見る

  When models are built with missing data, an information criterion is needed to select the best model among the various candidates. Using a conventional information criterion for missing data may lead to the selection of the wrong model when data are not missing at random. Conventional information criteria implicitly assume that any subset of missing-at-random data is also missing at random, and thus the maximum likelihood estimator is assumed to be consistent; that is, it is assumed that the estimator will converge to the true value. However, this assumption may not be practical. In this paper, we develop an information criterion that works even for not-missing-at-random data, so long as the largest missing data set is missing at random. Simulations are performed to show the superiority of the proposed information criterion over conventional criteria.

  • Access to Document (DOI)

• An Accelerated Failure Time Cure Model with Shifted Gamma Frailty and Its Application to Epidemiological Research

  Aida H., Hayashi K., Takeuchi A., Sugiyama D., Okamura T.

  Healthcare (Switzerland) （Healthcare (Switzerland)）  10 （ 8 ）  2022年08月

  査読有り

  　概要を見る

  Survival analysis is a set of methods for statistical inference concerning the time until the occurrence of an event. One of the main objectives of survival analysis is to evaluate the effects of different covariates on event time. Although the proportional hazards model is widely used in survival analysis, it assumes that the ratio of the hazard functions is constant over time. This assumption is likely to be violated in practice, leading to erroneous inferences and inappropriate conclusions. The accelerated failure time model is an alternative to the proportional hazards model that does not require such a strong assumption. Moreover, it is sometimes plausible to consider the existence of cured patients or long-term survivors. The survival regression models in such contexts are referred to as cure models. In this study, we consider the accelerated failure time cure model with frailty for uncured patients. Frailty is a latent random variable representing patients’ characteristics that cannot be described by observed covariates. This enables us to flexibly account for individual heterogeneities. Our proposed model assumes a shifted gamma distribution for frailty to represent uncured patients’ heterogeneities. We construct an estimation algorithm for the proposed model, and evaluate its performance via numerical simulations. Furthermore, as an application of the proposed model, we use a real dataset, Specific Health Checkups, concerning the onset of hypertension. Results from a model comparison suggest that the proposed model is superior to existing alternatives.

  • Access to Document (DOI)

• Pulmonary vein isolation alone vs. more extensive ablation with defragmentation and linear ablation of persistent atrial fibrillation: the EARNEST-PVI trial

  Inoue K., Hikoso S., Masuda M., Furukawa Y., Hirata A., Egami Y., Watanabe T., Minamiguchi H., Miyoshi M., Tanaka N., Oka T., Okada M., Kanda T., Matsuda Y., Kawasaki M., Hayashi K., Kitamura T., Dohi T., Sunaga A., Mizuno H., Nakatani D., Sakata Y.

  Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology （Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology）  23 （ 4 ） 565 - 574 2021年04月

  査読有り,  ISSN  10995129

  　概要を見る

  AIMS: Previous studies could not demonstrate any benefit of more intensive ablation in addition to pulmonary vein isolation (PVI) including complex fractionated atrial electrogram (CFAE) and linear ablation for recurrence in the initial catheter ablation of persistent atrial fibrillation (AF). This study aimed to establish the non-inferiority of PVI alone to PVI plus these additional ablation strategies. METHODS AND RESULTS: Patients with persistent AF who underwent an initial catheter ablation (n = 512, long-standing persistent AF; 128 cases) were randomly assigned in a 1:1 ratio to either PVI alone (PVI-alone group) or PVI plus CFAE and/or linear ablation (PVI-plus group). After excluding 15 cases who did not receive procedures, we analysed 249 and 248 patients, respectively. The primary endpoint was recurrence of AF, atrial flutter, and/or atrial tachycardia, and the non-inferior margin was set at a hazard ratio of 1.43. In the PVI-plus group, 85.1% of patients had linear ablation and 15.3% CFAE ablation. After 12 months, freedom from the primary endpoint occurred in 71.3% of patients in the PVI-alone group and in 78.3% in the PVI-plus group [hazard ratio = 1.56 (95% confidence interval: 1.10-2.24), non-inferior P = 0.3062]. The procedure-related complication rates were 2.0% in the PVI-alone group and 3.6% in the PVI-plus group (P = 0.199). CONCLUSION: This randomized trial did not establish the non-inferiority of PVI alone to PVI plus linear ablation or CFAE ablation in patients with persistent AF, but implied that the PVI plus strategy was promising to improve the clinical efficacy (NCT03514693).

  • Access to Document (DOI)

全件表示 >>

KOARA（リポジトリ）収録論文等 【 表示 ／ 非表示 】

KOARA（リポジトリ）収録論文等 【 表示 ／ 非表示 】

• 複雑な生命事象データにおける特異な部分集合の探索的同定に関する研究

  林, 賢一

  科学研究費補助金研究成果報告書 2017年

競争的研究費の研究課題 【 表示 ／ 非表示 】

競争的研究費の研究課題 【 表示 ／ 非表示 】

• 不均衡データに対する解析法の統合的理解と生存時間解析への発展的応用

  2023年04月

  -

  2027年03月

  林 賢一, 基盤研究(C), 補助金,  研究代表者

• 異質な集団を含むデータに対する統計的学習理論を用いたモデル開発と臨床医学への応用

  2018年04月

  -

  2022年03月

  文部科学省・日本学術振興会, 科学研究費助成事業, 林　賢一, 基盤研究(C), 補助金,  研究代表者

• 複雑な生命事象データにおける特異な部分集合の探索的同定に関する研究

  2015年04月

  -

  2018年03月

  文部科学省・日本学術振興会, 科学研究費助成事業, 林　賢一, 若手研究(B), 補助金,  研究代表者

受賞 【 表示 ／ 非表示 】

受賞 【 表示 ／ 非表示 】

• 最優秀賞（ポスター部門）

  岡田和也，林賢一, 2024年01月,  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

  受賞区分： 国内学会・会議・シンポジウム等の賞

  　説明を見る

  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年05月, 日本計量生物学会

  受賞区分： 国内学会・会議・シンポジウム等の賞

  　説明を見る

  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年01月, 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

  受賞区分： 国内学会・会議・シンポジウム等の賞

  　説明を見る

  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年12月, 日本分類学会, 日本分類学会

  受賞区分： 国内学会・会議・シンポジウム等の賞

• 論文賞

  2015年05月, 日本計算機統計学会, 日本計算機統計学会

  受賞区分： 国内学会・会議・シンポジウム等の賞

担当授業科目 【 表示 ／ 非表示 】

担当授業科目 【 表示 ／ 非表示 】

• 基礎理工学課題研究

  2024年度

• 基礎理工学特別研究第２

  2024年度

• 基礎理工学特別研究第１

  2024年度

• 卒業研究

  2024年度

• 統計科学特論Ｃ

  2023年度

全件表示 >>