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Prediction of pathological complete response to neoadjuvant chemotherapy in locally advanced breast cancer by using a deep learning model with 18F-FDG PET/CT.
Bulut, Gülcan; Atilgan, Hasan Ikbal; Çinarer, Gökalp; Kiliç, Kazim; Yikar, Deniz; Parlar, Tuba.
Afiliação
  • Bulut G; Division of Medical Oncology, International Medicana Hospital, Izmir, Turkey.
  • Atilgan HI; Department of Nuclear Medicine, Mustafa Kemal University Medical School, Hatay, Turkey.
  • Çinarer G; Department of Computer Engineering, Faculty of Engineering and Architecture, Bozok University, Yozgat, Turkey.
  • Kiliç K; Department of Computer Programming, Yozgat Vocational High School, Bozok University, Yozgat, Turkey.
  • Yikar D; Division of Nuclear Medicine, Hatay Training and Research Hospital, Hatay, Turkey.
  • Parlar T; Department of Computer Technologies, Mustafa Kemal University, Hatay, Türkiye.
PLoS One ; 18(9): e0290543, 2023.
Article em En | MEDLINE | ID: mdl-37708209
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Aprendizado Profundo Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans Idioma: En Revista: PLoS One Ano de publicação: 2023 Tipo de documento: Article
Texto completo
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XML
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Aprendizado Profundo Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans Idioma: En Revista: PLoS One Ano de publicação: 2023 Tipo de documento: Article