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Accurate deep learning model using semi-supervised learning and Noisy Student for cervical cancer screening in low magnification images.
Kurita, Yuki; Meguro, Shiori; Tsuyama, Naoko; Kosugi, Isao; Enomoto, Yasunori; Kawasaki, Hideya; Uemura, Takashi; Kimura, Michio; Iwashita, Toshihide.
Afiliação
  • Kurita Y; Department of Regenerative and Infectious Pathology, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan.
  • Meguro S; Department of Regenerative and Infectious Pathology, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan.
  • Tsuyama N; Division of Pathology, Cancer Institute, Japanese Foundation for Cancer Research, Tokyo, Japan.
  • Kosugi I; Department of Regenerative and Infectious Pathology, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan.
  • Enomoto Y; Department of Regenerative and Infectious Pathology, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan.
  • Kawasaki H; Institute for NanoSuit Research, Preeminent Medical Photonics Education & Research Center, Hamamatsu University School of Medicine, Hamamatsu, Japan.
  • Uemura T; Department of Pathology, JA Shizuoka Kohseiren Enshu Hospital, Hamamatsu, Shizuoka, Japan.
  • Kimura M; Department of Medical Informatics, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan.
  • Iwashita T; Department of Regenerative and Infectious Pathology, Hamamatsu University School of Medicine, Hamamatsu, Shizuoka, Japan.
PLoS One ; 18(5): e0285996, 2023.
Article em En | MEDLINE | ID: mdl-37200281
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias do Colo do Útero / Aprendizado Profundo / Lesões Intraepiteliais Escamosas Tipo de estudo: Diagnostic_studies / Prognostic_studies / Screening_studies Limite: Female / Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article
Texto completo
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XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias do Colo do Útero / Aprendizado Profundo / Lesões Intraepiteliais Escamosas Tipo de estudo: Diagnostic_studies / Prognostic_studies / Screening_studies Limite: Female / Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article