Professor Shigeyuki Matsui
Much of the medical research that focuses on human diseases faces significant uncertainty due to extremely complex biological mechanisms, large individual differences, as well as the limitations of research methods, including measurement. Biostatistics contributes to the development of medicine and healthcare through research and practice of data science methodologies to inductively infer the truth behind uncertain phenomena and predict future phenomena.
Research and Education
Our main research interests are in the design and data analysis of medical research involving human subjects. A particular area of focus has been the design and data analysis of clinical studies in personalized medicine, which combines diagnostics and therapies, with many research topics at the intersection of traditional statistical inference and recent machine learning methodologies. At the same time, we are also studying data science methodologies on various topics, including adaptive experimental designs in experimental studies with limited research resources, incorporation of external information through Bayesian modelling and transfer learning, and conditional inference that takes these adaptations into account. At the same time, as an expert in biostatistics, we participate and collaborate in many clinical studies in a wide range of disease areas.
Comments: Some of the books Prof. Matsui edited.
Recent Publications
- Matsui S, Igeta M. Phase II and III clinical trial designs for precision medicine. In Handbook of Statistics in Clinical Oncology, 4th Edition. (eds. J. Crowley, A. Hoering, M. Othus), CRC Press, in press, 2025.
- Emoto R, Igeta M, Matsui K, Ishii K, Takamura T, Matsui S. Evaluating treatment-effect modifiers using data from randomized two-sequence, two-period crossover clinical trials: Application to a diabetes study. Journal of the Royal Statistical Society, Series C, in press, 2025.
- Emoto R, Nishikimi M, Shoaib M, Hayashida K, Nishida K, Kikutani K, Ohshimo S, Matsui S, Shime N, Iwami T. Prediction of prehospital change of the cardiac rhythm from nonshockable to shockable in out-of-hospital patients with cardiac arrest: A post hoc analysis of a nationwide, multicenter, prospective registry. Journal of the American Heart Association 2022; 11(12): e025048.
- Matsui S, Crowley J. Biomarker-stratified phase III clinical trials: Enhancement with a subgroup-focused sequential design. Clin Cancer Res 2018; 24(5): 994-1001.
- Matsui S, Noma H, Qu P, Sakai Y, Matsui K, Heuck C, Crowley J. Multi-subgroup gene screening using semi-parametric hierarchical mixture models and the optimal discovery procedure: Application to a randomized clinical trial in multiple myeloma. Biometrics 2018; 74(1): 313-320.
Laboratory
Professor: Shigeyuki Matsui.
E-mail: contact@biostat.med.kyoto-u.ac.jp
URL : https://sites.google.com/view/kyoto-biostat?usp=sharing