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PROACTING: predicting pathological complete response to neoadjuvant chemotherapy in breast cancer from routine diagnostic histopathology biopsies with deep learning.
Aswolinskiy, Witali; Munari, Enrico; Horlings, Hugo M; Mulder, Lennart; Bogina, Giuseppe; Sanders, Joyce; Liu, Yat-Hee; van den Belt-Dusebout, Alexandra W; Tessier, Leslie; Balkenhol, Maschenka; Stegeman, Michelle; Hoven, Jeffrey; Wesseling, Jelle; van der Laak, Jeroen; Lips, Esther H; Ciompi, Francesco.
Afiliação
  • Aswolinskiy W; Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands.
  • Munari E; Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy.
  • Horlings HM; The Netherlands Cancer Institute (NKI), Amsterdam, The Netherlands.
  • Mulder L; The Netherlands Cancer Institute (NKI), Amsterdam, The Netherlands.
  • Bogina G; Pathology Unit, IRCCS Sacro Cuore Don Calabria Hospital, Negrar di Valpolicella, Verona, Italy.
  • Sanders J; The Netherlands Cancer Institute (NKI), Amsterdam, The Netherlands.
  • Liu YH; The Netherlands Cancer Institute (NKI), Amsterdam, The Netherlands.
  • van den Belt-Dusebout AW; The Netherlands Cancer Institute (NKI), Amsterdam, The Netherlands.
  • Tessier L; Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands.
  • Balkenhol M; Center for Integrated Oncology (Institut du cancer de l'Ouest), Angers, France.
  • Stegeman M; Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands.
  • Hoven J; Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands.
  • Wesseling J; Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands.
  • van der Laak J; The Netherlands Cancer Institute (NKI), Amsterdam, The Netherlands.
  • Lips EH; Leiden University Medical Center, Leiden, The Netherlands.
  • Ciompi F; Department of Pathology, Radboud University Medical Center, Nijmegen, The Netherlands.
Breast Cancer Res ; 25(1): 142, 2023 11 13.
Article em En | MEDLINE | ID: mdl-37957667
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Aprendizado Profundo Idioma: En Ano de publicação: 2023 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Aprendizado Profundo Idioma: En Ano de publicação: 2023 Tipo de documento: Article