Deep learning augmented pathological grading and intraductal carcinoma of the prostate signatures improve recurrence prediction after intensity-modulated radiation therapy

Mami Takadate, Rihito Aizawa, Yasushi Numata, Atsushi Marugame, Jyunya Iwazaki, Masao Ueki, Takayuki Takahashi, Kaori Ono, Kotaro Tsutsumi, Hayato Takeda, Jun Akatsuka, Yuki Endo, Yuka Toyama, Ryuji Ohashi, Akira Shimizu, Go Kimura, Hironori Haga, Takashi Kobayashi, Yukihiro Kondo, Takashi Mizowaki, Yoichiro Yamamoto, Toyonori Tsuzuki

Open source

DOI: 10.1007/s00428-026-04680-2
Published: 2026-08-28
Container: Virchows Archiv
Publisher: Springer Science and Business Media LLC
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1007/s00428-026-04680-2,
  title = {Deep learning augmented pathological grading and intraductal carcinoma of the prostate signatures improve recurrence prediction after intensity-modulated radiation therapy},
  author = {Mami Takadate and Rihito Aizawa and Yasushi Numata and Atsushi Marugame and Jyunya Iwazaki and Masao Ueki and Takayuki Takahashi and Kaori Ono and Kotaro Tsutsumi and Hayato Takeda and Jun Akatsuka and Yuki Endo and Yuka Toyama and Ryuji Ohashi and Akira Shimizu and Go Kimura and Hironori Haga and Takashi Kobayashi and Yukihiro Kondo and Takashi Mizowaki and Yoichiro Yamamoto and Toyonori Tsuzuki},
  year = {2026},
  journal = {Virchows Archiv},
  doi = {10.1007/s00428-026-04680-2},
  url = {https://doi.org/10.1007/s00428-026-04680-2}
}

RIS

TY  - JOUR
TI  - Deep learning augmented pathological grading and intraductal carcinoma of the prostate signatures improve recurrence prediction after intensity-modulated radiation therapy
AU  - Mami Takadate
AU  - Rihito Aizawa
AU  - Yasushi Numata
AU  - Atsushi Marugame
AU  - Jyunya Iwazaki
AU  - Masao Ueki
AU  - Takayuki Takahashi
AU  - Kaori Ono
AU  - Kotaro Tsutsumi
AU  - Hayato Takeda
AU  - Jun Akatsuka
AU  - Yuki Endo
AU  - Yuka Toyama
AU  - Ryuji Ohashi
AU  - Akira Shimizu
AU  - Go Kimura
AU  - Hironori Haga
AU  - Takashi Kobayashi
AU  - Yukihiro Kondo
AU  - Takashi Mizowaki
AU  - Yoichiro Yamamoto
AU  - Toyonori Tsuzuki
PY  - 2026
JO  - Virchows Archiv
DO  - 10.1007/s00428-026-04680-2
UR  - https://doi.org/10.1007/s00428-026-04680-2
ER  -

APA

Takadate, M., Aizawa, R., Numata, Y., Marugame, A., Iwazaki, J., Ueki, M., Takahashi, T., Ono, K., Tsutsumi, K., Takeda, H., Akatsuka, J., Endo, Y., Toyama, Y., Ohashi, R., Shimizu, A., Kimura, G., Haga, H., Kobayashi, T., Kondo, Y., Mizowaki, T., Yamamoto, Y., & Tsuzuki, T. (2026). Deep learning augmented pathological grading and intraductal carcinoma of the prostate signatures improve recurrence prediction after intensity-modulated radiation therapy. Virchows Archiv. https://doi.org/10.1007/s00428-026-04680-2

Source records

crossref · retrieved 2026-11-10T21:15:27.885Z