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RIKEN Center for Advanced Intelligence Project Data-Driven Biomedical Science Team

Team Leader: Ichiro Takeuchi (D.Eng.)

Research Summary

Ichiro  Takeuchi(D.Eng.)

In the field of biomedical science, rapid advances in measurement technology allow us to collect a massive scientific dataset. An attempt aiming for a new scientific discovery based on such a massive scientific dataset is now realized as the fourth scientific paradigm followed by traditional three approaches based on theory, experiment, and simulation. Using artificial intelligence and machine learning techniques, we have a chance to find novel scientific hypotheses which are difficult to obtain only from knowledge and experiences of human experts. In our team, we study fundamental computational and mathematical techniques for data-driven scientific discovery, and demonstrate the effectiveness of these techniques in the field of biomedical science.

Main Research Fields

  • Computer Science

Related Research Fields

  • Materials Sciences
  • Biology & Biochemistry
  • Molecular Biology & Genetics
  • Clinical Medicine
  • Mathematics

Research Subjects

  • Data Science

Selected Publications

  • 1. Shiraishi T., Miwa D., Katsuoka T., Duy V.N.L., Taji K., Takeuchi I.:
    "Statistical Test for Attention Maps in Vision Transformers"
    International Conference on Machine Learning (2024)
  • 2. Duy V.N.L., Lin H.T., Takeuchi I.:
    "CAD-DA: Controllable Anomaly Detection after Domain Adaptation by Statistical Inference"
    AI&Statistics (2024)
  • 3. Goto K., Tamehiro N., Yoshida T., Hanada H., Sakuma T., Adachi R., Kondo K., Takeuchi I.:
    "Novel Machine Learning Method AllerStat Identifies Statistically Significant Allergen-Specific Patterns in Protein Sequences."
    Journal of Biological Chemistry. Vol.299-6, 104733 (2023)
  • 4. Hashimoto N., Takagi Y., Masuda H., Miyoshi H., Kohno K., Nagaishi M., Sato K., Takeuchi M., Furuta T., Kawamoto K., Yamada K., Moritsubo M., Inoue K., Shimasaki Y., Ogura Y., Imamoto T., Mishina T., Tanaka K., Kawaguchi Y., Nakamura S., Ohshima K., Hontani H., Takeuchi I.:
    "Case-based Similar Image Retrieval for Weakly Annotated Large Histopathological Images of Malignant Lymphoma Using Deep Metric Learning."
    Medical Image Analysis. Vol.85 (2023)
  • 5. Kato H., Hanada H., Takeuchi I.:
    "Safe RuleFit: Learning Optimal Sparse Rule Model by Meta Safe Screening."
    IEEE Transactions on Pattern Analysis and Machine Intelligence. Vol.45-2, pp.2330-2343 (2023)
  • 6. Miwa D., Duy V.N.L., Takeuchi I.:
    "Valid P-Value for Deep Learning-driven Salient Region"
    The International Conference on Learning Representation (2023)
  • 7. Ndiaye E., Takeuchi I.:
    "Root-finding Approaches for Computing Conformal Prediction Set"
    Machine Learning (2022)
  • 8. Duy V.N.L., Takeuchi I.:
    "More Powerful Conditional Selective Inference for Generalized Lasso by Parametric Programming."
    Journal of Machine Learning Research. Vol.23(300) (2022)
  • 9. Duy V.N.L., Iwazaki S., Takeuchi I.:
    "Quantifying Statistical Significance of Neural Network-based Image Segmentation by Selective Inference."
    Neural Information Processing Systems (2022)
  • 10. Inatsu Y., Takeno S., Karasuyama M., Takeuchi I.:
    "Bayesian Optimization for Distributionally Robust Chance-constrained Problem."
    International Conference on Machine Learning (2022)

Related Links

Lab Members

Principal investigator

Ichiro Takeuchi
Team Leader

Core members

Hiroyuki Hanada
Research Scientist
Noriaki Hashimoto
Research Scientist
Shigeyuki Matsui
Senior Visiting Scientist
Toru Ujihara
Visiting Scientist
Keiichi Inoue
Visiting Scientist
Vo Nguyen Le Duy
Visiting Scientist
Shion Takeno
Visiting Scientist
Kentaro Kutsukake
Visiting Scientist
Shuichi Nishino
Junior Research Associate
Xudong Chen
Research Part-time Worker I
Onur Boyar
Research Part-time Worker I

Contact Information

#427 4th Floor Bldg. 2, Nagoya University, Furo-cho, Chikusa-ku,
Nagoya, Aichi,
464-8603, Japan
Email: ichiro.takeuchi@riken.jp

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