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HRD-related morphology discovery in breast cancer by controlling for confounding factors
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.
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9798077/ https://www.ncbi.nlm.nih.gov/pubmed/36543118 http://dx.doi.org/10.1016/j.xcrm.2022.100873 |
_version_ | 1784860828057468928 |
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author | Schirris, Yoni Horlings, Hugo Mark |
author_facet | Schirris, Yoni Horlings, Hugo Mark |
author_sort | Schirris, Yoni |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9798077 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-97980772022-12-30 HRD-related morphology discovery in breast cancer by controlling for confounding factors Schirris, Yoni Horlings, Hugo Mark Cell Rep Med Preview 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. Elsevier 2022-12-20 /pmc/articles/PMC9798077/ /pubmed/36543118 http://dx.doi.org/10.1016/j.xcrm.2022.100873 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Preview Schirris, Yoni Horlings, Hugo Mark HRD-related morphology discovery in breast cancer by controlling for confounding factors |
title | HRD-related morphology discovery in breast cancer by controlling for confounding factors |
title_full | HRD-related morphology discovery in breast cancer by controlling for confounding factors |
title_fullStr | HRD-related morphology discovery in breast cancer by controlling for confounding factors |
title_full_unstemmed | HRD-related morphology discovery in breast cancer by controlling for confounding factors |
title_short | HRD-related morphology discovery in breast cancer by controlling for confounding factors |
title_sort | hrd-related morphology discovery in breast cancer by controlling for confounding factors |
topic | Preview |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9798077/ https://www.ncbi.nlm.nih.gov/pubmed/36543118 http://dx.doi.org/10.1016/j.xcrm.2022.100873 |
work_keys_str_mv | AT schirrisyoni hrdrelatedmorphologydiscoveryinbreastcancerbycontrollingforconfoundingfactors AT horlingshugomark hrdrelatedmorphologydiscoveryinbreastcancerbycontrollingforconfoundingfactors |