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Relationship between a deep learning model and liquid-based cytological processing techniques.
Ikeda, Katsuhide; Sakabe, Nanako; Maruyama, Sayumi; Ito, Chihiro; Shimoyama, Yuka; Oboshi, Wataru; Komene, Tetsuya; Yamaguchi, Yoshitaka; Sato, Shouichi; Nagata, Kohzo.
Afiliación
  • Ikeda K; Pathophysiology Sciences, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan.
  • Sakabe N; Pathophysiology Sciences, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan.
  • Maruyama S; Pathophysiology Sciences, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan.
  • Ito C; Pathophysiology Sciences, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan.
  • Shimoyama Y; Pathophysiology Sciences, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan.
  • Oboshi W; Department of Medical Technology and Sciences, School of Health Sciences at Narita, International University of Health and Welfare, Narita, Japan.
  • Komene T; Department of Medical Technology and Sciences, School of Health Sciences at Narita, International University of Health and Welfare, Narita, Japan.
  • Yamaguchi Y; Department of Medical Technology and Sciences, School of Health Sciences at Narita, International University of Health and Welfare, Narita, Japan.
  • Sato S; Clinical Engineering, Faculty of medical sciences, Juntendo University, Urayasu, Japan.
  • Nagata K; Pathophysiology Sciences, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Cytopathology ; 34(4): 308-317, 2023 07.
Article en En | MEDLINE | ID: mdl-37051774
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Aprendizaje Profundo Límite: Humans Idioma: En Revista: Cytopathology Asunto de la revista: PATOLOGIA Año: 2023 Tipo del documento: Article País de afiliación: Japón Pais de publicación: Reino Unido
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Aprendizaje Profundo Límite: Humans Idioma: En Revista: Cytopathology Asunto de la revista: PATOLOGIA Año: 2023 Tipo del documento: Article País de afiliación: Japón Pais de publicación: Reino Unido