Unsupervised Brain Abnormality Detection Using High Fidelity Image Reconstruction Networks. - Kazuma Kobayashi; Ryuichiro Hataya; Yusuke Kurose; Amina Bolatkan; Mototaka Miyake; Hirokazu Watanabe; Masamichi Takahashi; Naoki Mihara; Jun Itami; Tatsuya Harada; Ryuji Hamamoto (CoRR, 2020)

Decomposing Normal and Abnormal Features of Medical Images for Content-based Image Retrieval. - Kazuma Kobayashi; Ryuichiro Hataya; Yusuke Kurose; Tatsuya Harada; Ryuji Hamamoto (CoRR, 2020)

Decomposing Normal and Abnormal Features of Medical Images into Discrete Latent Codes for Content-Based Image Retrieval. - Kazuma Kobayashi; Ryuichiro Hataya; Yusuke Kurose; Mototaka Miyake; Masamichi Takahashi; Akiko Nakagawa; Tatsuya Harada; Ryuji Hamamoto (CoRR, 2021)

Decomposing normal and abnormal features of medical images for content-based image retrieval of glioma imaging. - Kazuma Kobayashi; Ryuichiro Hataya; Yusuke Kurose; Mototaka Miyake; Masamichi Takahashi; Akiko Nakagawa; Tatsuya Harada; Ryuji Hamamoto (Medical Image Anal., 2021)

Application of non-negative matrix factorization in oncology: one approach for establishing precision medicine. - Ryuji Hamamoto; Ken Takasawa; Hidenori Machino; Kazuma Kobayashi; Satoshi Takahashi; Amina Bolatkan; Norio Shinkai; Akira Sakai; Rina Aoyama; Masayoshi Yamada; Ken Asada; Masaaki Komatsu; et al. (Briefings Bioinform., 2022)

Towards AI-Driven Radiology Education: A Self-supervised Segmentation-Based Framework for High-Precision Medical Image Editing. - Kazuma Kobayashi; Lin Gu 003; Ryuichiro Hataya; Mototaka Miyake; Yasuyuki Takamizawa; Sono Ito; Hirokazu Watanabe; Yukihiro Yoshida; Hiroki Yoshimura; Tatsuya Harada; Ryuji Hamamoto (MICCAI (2), 2023)

Sketch-based Medical Image Retrieval. - Kazuma Kobayashi; Lin Gu 003; Ryuichiro Hataya; Takaaki Mizuno; Mototaka Miyake; Hirokazu Watanabe; Masamichi Takahashi; Yasuyuki Takamizawa; Yukihiro Yoshida; Satoshi Nakamura; Nobuji Kouno; Amina Bolatkan; et al. (CoRR, 2023)

Analysis of super-enhancer using machine learning and its application to medical biology. - Ryuji Hamamoto; Ken Takasawa; Norio Shinkai; Hidenori Machino; Nobuji Kouno; Ken Asada; Masaaki Komatsu; Syuzo Kaneko (Briefings Bioinform., 2023)

Can physician judgment enhance model trustworthiness? A case study on predicting pathological lymph nodes in rectal cancer. - Kazuma Kobayashi; Yasuyuki Takamizawa; Mototaka Miyake; Sono Ito; Lin Gu 003; Tatsuya Nakatsuka; Yu Akagi; Tatsuya Harada; Yukihide Kanemitsu; Ryuji Hamamoto (Artif. Intell. Medicine, 2024)

Sketch-based semantic retrieval of medical images. - Kazuma Kobayashi; Lin Gu 003; Ryuichiro Hataya; Takaaki Mizuno; Mototaka Miyake; Hirokazu Watanabe; Masamichi Takahashi; Yasuyuki Takamizawa; Yukihiro Yoshida; Satoshi Nakamura; Nobuji Kouno; Amina Bolatkan; et al. (Medical Image Anal., 2024)

Comparison of Vision Transformers and Convolutional Neural Networks in Medical Image Analysis: A Systematic Review. - Satoshi Takahashi; Yusuke Sakaguchi; Nobuji Kouno; Ken Takasawa; Kenichi Ishizu; Yu Akagi; Rina Aoyama; Naoki Teraya; Amina Bolatkan; Norio Shinkai; Hidenori Machino; Kazuma Kobayashi; et al. (J. Medical Syst., 2024)

Establishment of a machine learning model for predicting splenic hilar lymph node metastasis. - Kenichi Ishizu; Satoshi Takahashi; Nobuji Kouno; Ken Takasawa; Katsuji Takeda; Kota Matsui; Masashi Nishino; Tsutomu Hayashi; Yukinori Yamagata; Shigeyuki Matsui; Takaki Yoshikawa; Ryuji Hamamoto (npj Digit. Medicine, 2025)

A series of natural language processing for predicting tumor response evaluation and survival curve from electronic health records. - Toshiki Takeuchi; Hidehito Horinouchi; Ken Takasawa; Masami Mukai; Ken Masuda; Yuki Shinno; Yusuke Okuma; Tatsuya Yoshida; Yasushi Goto; Noboru Yamamoto; Yuichiro Ohe; Mototaka Miyake; et al. (BMC Medical Informatics Decis. Mak., 2025)