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HRD-related morphology discovery in breast cancer by controlling for confounding factors.
Schirris, Yoni; Horlings, Hugo Mark.
Affiliation
  • Schirris Y; Netherlands Cancer Institute, Plesmanlaan 121, Amsterdam, CX 1066, the Netherlands; University of Amsterdam, Science Park 402, Amsterdam, XH 1098, the Netherlands.
  • Horlings HM; Netherlands Cancer Institute, Plesmanlaan 121, Amsterdam, CX 1066, the Netherlands. Electronic address: h.horlings@nki.nl.
Cell Rep Med ; 3(12): 100873, 2022 12 20.
Article in En | MEDLINE | ID: mdl-36543118
Lazard et al.1 predict homologous recombination deficiency from hematoxylin and eosin-stained slides of breast cancer tissue using deep learning. By controlling for technical artifacts on a curated dataset, the model puts forward novel HRD-related morphologies in luminal breast cancers.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Breast Neoplasms Type of study: Prognostic_studies Limits: Female / Humans Language: En Journal: Cell Rep Med Year: 2022 Document type: Article Affiliation country: Country of publication:
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Breast Neoplasms Type of study: Prognostic_studies Limits: Female / Humans Language: En Journal: Cell Rep Med Year: 2022 Document type: Article Affiliation country: Country of publication: