Experts
研究者

米岡 大輔/Daisuke Yoneoka

米岡 大輔 Daisuke Yoneoka

  • 主席研究員

聖路加国際大学で、個別化医療のための生物統計学と機械学習の理論的側面に取り組む。2016年に総合研究大学院大学で博士号(統計学)を取得し、米国(セント・ジュード子供研究病院)とスイス(ETHチューリッヒ)でポスドクを開始。 生物統計学と機械学習の分野に広く興味を持っており、特に個別化医療への応用に力を入れている。数学・統計学を医学・疫学・公衆衛生に応用することも研究対象としている。

【兼 職】
聖路加国際大学公衆衛生大学院准教授

研究分野・主な関心領域

  • 生物統計
  • 機械学習
  • 理論疫学
  • 空間統計
  • 公衆衛生

研究プログラム

ヘルス・メトリクスを用いた政策インパクトのモニタリングと評価に関する研究


主な著作等

  1. Daisuke Yoneoka, Takayuki Kawashima, Koji Makiyama, Yuta Tanoue, Shuhei Nomura, and Akifumi Eguchi. Geographically weighted generalized Farrington algorithm for rapid outbreak detection over short data accumulation periods. Statistics in Medicine. 2021; 1– 18.
  2. Daisuke Yoneoka (co-first), Tomohide Yamada, Yuta Hiraike, Kimihiro Hino, Hiroyoshi Toyoshiba, Akira Shishido, Hisashi Noma, Nobuhiro Shojima, and Toshimasa Yamauchi. Deep neural network-based machine learning reduces the screening workload for systematic review: Investigation based on recentclinical guidelines. Journal of Medical Internet Research, 2020.
  3. Shoi Shi, Shiori Tanaka, Ryo Ueno, Stuart Gilmour, Yuta Tanoue, Takayuki Kawashima, Shuhei Nomura, Akifumi Eguchi, Hiroaki Miyata, and Daisuke Yoneoka. Travel restrictions and SARS-CoV-2 transmission: An effective distance approach to estimate impact. Bulletin of the World Health Organization, 98(8):518, 2020.
  4. Daisuke Yoneoka (co-first), Shuhei Nomura, Shoi Shi, Yuta Tanoue, Takayuki Kawashima, Akifumi Eguchi, Kentaro Matsuura, Koji Makiyama, Keisuke Ejima, Toshibumi Taniguchi, Haruka Sakamoto, Hiroyuki Kunishima, Stuart Gilmour, Hiroshi Nishiura, and Hiroaki Miyata. An assessment of self-reported covid-19 related symptoms of 227,898 users of a social networking service in Japan: Has the regional risk changed after the declaration of the state of emergency? The Lancet Regional Health-Western Pacific, 1:100011, 2020.
  5. Daisuke Yoneoka (co-first), Takayuki Kawashima, Yuta Tanoue, Shuhei Nomura, Keisuke Ejima, Shoi Shi, Akifumi Eguchi, Toshibumi Taniguchi, Haruka Sakamoto, Hiroyuki Kunishima, Stuart Gilmour, Hiroshi Nishiura, and Hiroaki Miyata. Early SNS-based monitoring system for the COVID-19 outbreak in Japan: A population-level observational study. Journal of Epidemiology, page JE20200150, 2020.
  6. Daisuke Yoneoka, Cindy Im, and Yutaka Yasui. Parallel repulsive logicre gression with biological adjacency. Biostatistics, 21(4):825–844, 2020.
  7. Daisuke Yoneoka (Co-first), Yuta Tanoue, Takayuki Kawashima, Shuhei Nomura, Shoi Shi, Akifumi Eguchi, Keisuke Ejima, Toshibumi Taniguchi, Haruka Sakamoto, Hiroyuki Kunishima, Stuart Gilmour, Hiroshi Nishiura, and Hiroaki Miyata. Large-scale epidemiological monitoring of the covid-19 epidemic in Tokyo. The Lancet Regional Health-Western Pacific, 3:100016, 2020.
  8. Daisuke Yoneoka and Masayuki Henmi. Clinical heterogeneity in random-effect meta-analysis: Between-study boundary estimate problem. Statisticsin Medicine, 20;38(21):4131-4145 2019.
  9. Daisuke Yoneoka and Masayuki Henmi. Meta-analytical synthesis of regression coefficients under different categorization scheme of continuouscovariates. Statistics in medicine, 36(27):4336–4352, 2017.
  10. Daisuke Yoneoka and Masayuki Henmi. Synthesis of linear regression co-efficients by recovering the within-study covariance matrix from summarystatistics. Research synthesis methods, 8(2):212–219, 2017.
  11. Daisuke Yoneoka, Eiko Saito, and Shinji Nakaoka. New algorithm for con-structing area-based index with geographical heterogeneities and variableselection: An application to gastric cancer screening. Scientific reports, 6(1):1–7, 2016.
  12. Daisuke Yoneoka and Eiko Saito. A statistical note on analyzing and interpreting individual-level epidemiological data. Journal of Epidemiology, 25(4):337–338, 2015.
  13. Daisuke Yoneoka, Masayuki Henmi, Norie Sawada, and Manami Inoue. Synthesis of clinical prediction models under different sets of covariates withone individual patient data. BMC Medical Research Methodology, 15(1):1–11, 2015.