J
Junko Fujisaki
Researcher at Japanese Foundation for Cancer Research
Publications - 188
Citations - 5004
Junko Fujisaki is an academic researcher from Japanese Foundation for Cancer Research. The author has contributed to research in topics: Cancer & Early Gastric Cancer. The author has an hindex of 29, co-authored 169 publications receiving 3693 citations.
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Journal ArticleDOI
Application of artificial intelligence using a convolutional neural network for detecting gastric cancer in endoscopic images.
Toshiaki Hirasawa,Kazuharu Aoyama,Tetsuya Tanimoto,Soichiro Ishihara,Satoki Shichijo,Tsuyoshi Ozawa,Tatsuya Ohnishi,Mitsuhiro Fujishiro,Keigo Matsuo,Junko Fujisaki,Tomohiro Tada +10 more
TL;DR: The constructed CNN system for detecting gastric cancer could process numerous stored endoscopic images in a very short time with a clinically relevant diagnostic ability and may be well applicable to daily clinical practice to reduce the burden of endoscopists.
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Incidence of lymph node metastasis and the feasibility of endoscopic resection for undifferentiated-type early gastric cancer.
Toshiaki Hirasawa,Takuji Gotoda,Satoshi Miyata,You Kato,Tadakazu Shimoda,Hirokazu Taniguchi,Junko Fujisaki,Takeshi Sano,Toshiharu Yamaguchi +8 more
TL;DR: UD-type intramucosal EGC 20 mm or less in size without lymphatic-vascular capillary involvement and ulcerative findings presents a negligible risk of lymph node metastasis, and it is proposed that in this circumstance ER could be considered.
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A multicenter retrospective study of endoscopic resection for early gastric cancer
Ichiro Oda,Daizo Saito,Masahiro Tada,Hiroyasu Iishi,Satoshi Tanabe,Tsuneo Oyama,Toshihiko Doi,Yoshihide Otani,Junko Fujisaki,Yoichi Ajioka,Tsutomu Hamada,Haruhiro Inoue,Takuji Gotoda,Shigeaki Yoshida +13 more
TL;DR: ER leads to an excellent 3-year survival in clinical practice and could be a possible standard treatment for EGC, and ESD has the advantage of achieving one-piece resection and reducing local residual or recurrent tumor.
Journal ArticleDOI
Diagnostic outcomes of esophageal cancer by artificial intelligence using convolutional neural networks
Yoshimasa Horie,Toshiyuki Yoshio,Kazuharu Aoyama,Shoichi Yoshimizu,Yusuke Horiuchi,Akiyoshi Ishiyama,Toshiaki Hirasawa,Tomohiro Tsuchida,Tsuyoshi Ozawa,Soichiro Ishihara,Youichi Kumagai,Mitsuhiro Fujishiro,Iruru Maetani,Junko Fujisaki,Tomohiro Tada +14 more
TL;DR: The constructed CNN system for detecting esophageal cancer can analyze stored endoscopic images in a short time with high sensitivity, however, more training would lead to higher diagnostic accuracy.
Journal ArticleDOI
Risk factors for delayed bleeding after endoscopic submucosal dissection for gastric neoplasm
Kazuhisa Okada,Yorimasa Yamamoto,Akiyoshi Kasuga,Masami Omae,Manabu Kubota,Toshiaki Hirasawa,Akiyoshi Ishiyama,Akiko Chino,Tomohiro Tsuchida,Junko Fujisaki,Atsushi Nakajima,Etsuo Hoshino,Masahiro Igarashi +12 more
TL;DR: Risk factors for delayed bleeding, and the probable underlying mechanism involved, differed depending on the time elapsed between surgery and the bleeding episode.