no code implementations • 30 May 2024 • Taisei Tosaki, Eiichiro Uchino, Ryosuke Kojima, Yohei Mineharu, Mikio Arita, Nobuyuki Miyai, Yoshinori Tamada, Tatsuya Mikami, Koichi Murashita, Shigeyuki Nakaji, Yasushi Okuno
To evaluate the ODROP method, we trained disease onset prediction models and OOD detection models on Hirosaki data and used AUROC-rejection curve plots from Wakayama data.
no code implementations • 21 Jul 2023 • Aya Nakamura, Ryosuke Kojima, Yuji Okamoto, Eiichiro Uchino, Yohei Mineharu, Yohei Harada, Mayumi Kamada, Manabu Muto, Motoko Yanagita, Yasushi Okuno
This framework enables learning, visualizing, and clustering of temporal changes in patient latent states related to disease progression.
no code implementations • 29 Jun 2023 • Kazuma Inoue, Ryosuke Kojima, Mayumi Kamada, Yasushi Okuno
We applied this framework to cancer prognosis prediction using gene expression data and a biological network.
no code implementations • 21 Dec 2022 • Atsuko Takagi, Mayumi Kamada, Eri Hamatani, Ryosuke Kojima, Yasushi Okuno
GraphIX is a framework for evidence-based drug discovery that can present to users new disease-drug associations and identify the protein important for understanding its pharmacological effects from a large and complex knowledge base.
no code implementations • 31 May 2022 • Kazuki Nakamura, Eiichiro Uchino, Noriaki Sato, Ayano Araki, Kei Terayama, Ryosuke Kojima, Koichi Murashita, Ken Itoh, Tatsuya Mikami, Yoshinori Tamada, Yasushi Okuno
Here, we present the health-disease phase diagram (HDPD), which represents a personal health state by visualizing the boundary values of multiple biomarkers that fluctuate early in the disease progression process.
no code implementations • 30 Oct 2020 • Kazuki Nakamura, Ryosuke Kojima, Eiichiro Uchino, Koichi Murashita, Ken Itoh, Shigeyuki Nakaji, Yasushi Okuno
A key point of the framework is the evaluation of the "actionability" for personal health improvements by using a surrogate Bayesian model in addition to a high-performance nonlinear ML model.
no code implementations • 21 Aug 2020 • Yoshihisa Tanaka, Kako Higashihara, Mai Adachi Nakazawa, Fumiyoshi Yamashita, Yoshinori Tamada, Yasushi Okuno
This investigation process is indispensable for an understanding of how SARS-CoV-2 behaves in human host cells.
1 code implementation • 6 Dec 2018 • Kei Terayama, Ryo Tamura, Yoshitaro Nose, Hidenori Hiramatsu, Hideo Hosono, Yasushi Okuno, Koji Tsuda
Furthermore, we show that using the US approach, undetected new phase can be rapidly found, and smaller number of initial sampling points are sufficient.
Materials Science Computational Physics