Yoshitaka KAMEYA

Associate Professor at Department of Information Engineering, Faculty of Information Engineering, Meijo University

Research area

Artificial intelligence (knowledge engineering, machine learning, data mining, or explainable AI)

Contact information

Address:

Department of Information Engineering,
Faculty of Information Engineering,
Meijo University,
1-501 Shiogama-guchi, Tenpaku-ku, Nagoya, Aichi 468-8502, Japan

Room:

R3-329, Laboratory Bldg. 3, Tenpaku Campus

Phone:

+81-52-838-2567

E-mail:

ykameya [at] meijo-u.ac.jp

Lectures

• Databases
• Operating Systems
• Introduction to Project-Based Learning
• Advanced Project-Based Experiments 2
• Advanced Intelligent Data Analysis (for graduate students)

Dissertation

Publications (peer-reviewed)

• Matsumoto, N., Mizuno, T., Ando, Y., Kato, K., Nakanishi, M., Nakai, T., Lee, J. K., Kameya, Y., Nakamura, W., Takahara, K., Shiroki, R., and Yamada, S.: Prediction model for severe thrombocytopenia induced by gemcitabine plus cisplatin combination therapy in patients with urothelial cancer, Clinical Drug Investigation, Vol. 44, pp. 357–366, 2024. [paper] (Springer)
• Hasegawa, S., Mizokami, F., Mizuno, T., Yabu, T., Kameya, Y., Hayakawa, Y., and Arai, H.: Investigation of geriatric syndromes associated with medication in Japan using insurance claims data, Geriatrics & Gerontology International, Vol. 24, Issue 1, pp. 61–67, 2023. [paper] (Wiley)
• Hasegawa, S., Mizokami, F., Kameya, Y., Hayakawa, Y., Watanabe, T., and Matsui, Y.: Machine learning versus binomial logistic regression analysis for fall risk based on SPPB scores in older adult outpatients, Digital Health, Vol. 9, 2023. [paper] (Sage)
• Sassa, N., Kameya, Y., Takahashi, T., Matsukawa, Y., Majima, T., Tsuruta, K., Kobayashi, I., Kajikawa, K., Kawanishi, H., Kurosu, H., Yamagiwa, S., Takahashi, M., Hotta, K., Yamada, K., and Yamamoto, T.: Creation of synthetic contrast-enhanced computed tomography images using deep neural networks to screen for renal cell carcinoma, Nagoya Journal of Medical Science, Vol. 85, No. 4, pp. 713–724, 2023. [paper] (Nagoya U.)
• Tanaka, T., Fukazawa, T., Kameya, Y., Yamada, K., Hotta, K., Takahashi, T., Sassa, N., Matsukawa, Y., Iwano, S., Yamamoto, T.: Kidney cancer detection from CT images by Transformer-based classifiers. Proceedings of the 14th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI-2023), pp. 456–461, 2023. Received Honorable Mention Award. [paper] (IEEE Xplore) [slides]
• Nishizawa, T., Hanabusa, S., Kameya, Y., Takahashi, K., Tsuboi, N., and Mizuno, T.: Ante- and post-hoc explanations for prediction models of cisplatin-induced acute kidney injury: A comparative study. Proceedings of the 7th International Conference on Medical and Health Informatics (ICMHI-2023), pp. 66–71, 2023. [paper] (ACM DL)
• Matsukawa, Y., Kameya, Y., Takahashi, T., Shimazu, A., Ishida, S., Yamada, M., Sassa, N., and Yamamoto, T.: Characteristics of uroflowmetry patterns in men with detrusor underactivity revealed by artificial intelligence. International Journal of Urology, Vol. 30, Issue 10, pp. 907–912, 2023. [paper] (Wiley)
• Okawa, T., Mizuno, T., Hanabusa, S., Ikeda, T., Mizokami, F., Koseki, T., Takahashi, K., Yuzawa, Y., Tsuboi, N., Yamada, S., and Kameya, Y.: Prediction model of acute kidney injury induced by Cisplatin in older adults using a machine learning algorithm. PLOS ONE, Vol. 17, No. 1, e0262021, 2022. [paper] (PLOS ONE)
• Sakurai, K. and Kameya, Y.: Shared-memory parallelization of FP-growth with dynamic load estimation and balancing. Proceedings of the 12th International Workshop on Computational Intelligence and Applications (IWCIA-2021), 2021. [paper] (IEEE Xplore)
• Matsukawa, Y., Kameya, Y., Takahashi, T., Shimazu, A., Ishida, S., Yamada, M., Sassa, N., and Yamamoto, T.: Development of an artificial intelligence diagnostic system for lower urinary tract dysfunction in men. International Journal of Urology, Vol. 28, Issue 11, pp. 1143–1148, 2021. [paper] (Wiley)
• Suzuki, M., Kameya, Y., Kutsuna, T., and Mitsumoto, N.: Understanding the reason for misclassification by generating counterfactual images. Proceedings of the 17th International Conference on Machine Vision Applications (MVA-2021), 2021. Received Best Poster Award. [paper] (MVA) [paper] (IEEE Xplore) [paper] (Self-archive)
• Takahashi, M., Kameya, Y., Yamada, K., Hotta, K., Takahashi, T., Sassa, N., Iwano, S. and Yamamoto, T.: An empirical study on the use of visual explanation in kidney cancer detection. Proceedings of the 12th International Conference on Digital Image Processing (ICDIP-2020), 2020. [paper] (SPIE) [paper] (Self-archive)
• Maeda, K. and Kameya, Y.: Associative classification using common instances among conflicting discriminative patterns. Proceedings of the 2019 International Conference on Technologies and Applications of Artificial Intelligence (TAAI-2019), 2019. [paper] (IEEE Xplore) [paper] (Self-archive)
• Tsunakawa, H., Kameya, Y., Lee, H., Shinya, Y. and Mitsumoto, N.: Contrastive relevance propagation for interpreting predictions by a single-shot object detector. Proceedings of the 2019 International Joint Conference on Neural Networks (IJCNN-2019), 2019. [paper] (IEEE Xplore) [slides]
• Kameya, Y. and Ito, K.: Dynamic re-ordering in mining top-k productive discriminative patterns. Proceedings of the 2017 International Conference on Technologies and Applications of Artificial Intelligence (TAAI-2017), pp. 172–177, 2017. [paper] (IEEE Xplore) [paper] (Self-archive) [slides]
• Kameya, Y.: An exhaustive covering approach to parameter-free mining of non-redundant discriminative itemsets. Proceedings of the 18th International Conference on Big Data Analytics and Knowledge Discovery (DaWaK-2016), pp. 143–159, 2016. [paper] (Springer) [paper] (Self-archive) [slides]
• Kameya, Y. and Hayashi, K.: Bottom-up cell suppression that preserves the missing-at-random condition. Proceedings of the 13th International Conference on Trust, Privacy, and Security in Digital Business (TrustBus-2016), pp. 65–78, 2016. [paper] (Springer) [paper] (Self-archive) [slides]

Publications (unreviewed)

• Sassa, N., Kameya, Y., Takahashi, T., Matsukawa, Y., Majima, T., Tsuruta, K., Kobayashi, I., Kajikawa, K., Kawanishi, H., Kurosu, H., Yamagiwa, S., Takahashi, M., Hotta, K., Yamada, K., and Yamamoto, T.: Creation of Synthetic Contrast-Enhanced Computed Tomography Images Using Deep Neural Networks to Screen for Renal Cell Carcinoma, medRxiv:2022.01.12.22269120, January, 2022.

Awards

• Honorable Mention Award at the 14th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI-2023) — Tanaka, T., Fukazawa, T., Kameya, Y., Yamada, K., Hotta, K., Takahashi, T., Sassa, N., Matsukawa, Y., Iwano, S., Yamamoto, T.: Kidney cancer detection from CT images by Transformer-based classifiers.
• Best Poster Award at the 17th International Conference on Machine Vision Applications (MVA-2021) — Suzuki, M., Kameya, Y., Kutsuna, T., and Mitsumoto, N.: Understanding the reason for misclassification by generating counterfactual images.

Software

• PRISM — Prolog-based programming language for probabilistic modeling
• NBCTK — General-purpose probabilistic clustering tool

Links

• Archives of Sato Lab. at Tokyo Tech

Last update: July 21, 2024