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Deep learning-based automated quantification of goblet cell mucus using histological images as a predictor of clinical relapse of ulcerative colitis with endoscopic remission.
Ohara, Jun; Nemoto, Tetsuo; Maeda, Yasuharu; Ogata, Noriyuki; Kudo, Shin-Ei; Yamochi, Toshiko.
Affiliation
  • Ohara J; Department of Pathology, Showa University, Tokyo, Japan. johara1729@med.showa-u.ac.jp.
  • Nemoto T; Department of Pathology and Laboratory Medicine, Showa University Northern Yokohama Hospital, Kanagawa, Japan.
  • Maeda Y; Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan.
  • Ogata N; Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan.
  • Kudo SE; Digestive Disease Center, Showa University Northern Yokohama Hospital, Kanagawa, Japan.
  • Yamochi T; Department of Pathology, Showa University, Tokyo, Japan.
J Gastroenterol ; 57(12): 962-970, 2022 12.
Article in En | MEDLINE | ID: mdl-36184701
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Colitis, Ulcerative / Goblet Cells / Deep Learning / Mucins Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: J Gastroenterol Journal subject: GASTROENTEROLOGIA Year: 2022 Document type: Article Affiliation country: Japón
Fulltext
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Colitis, Ulcerative / Goblet Cells / Deep Learning / Mucins Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: J Gastroenterol Journal subject: GASTROENTEROLOGIA Year: 2022 Document type: Article Affiliation country: Japón