Quantitative digital histopathology and machine learning to predict pathological complete response to chemotherapy in breast cancer patients using pre-treatment tumor biopsies

Complete pathological response (pCR) to neoadjuvant chemotherapy (NAC) is a prognostic factor for breast cancer (BC) patients and is correlated with improved survival. However, pCR rates are variable to standard NAC, depending on BC subtype. This study investigates quantitative digital histopatholog...

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Detalles Bibliográficos
Autores principales: Saednia, Khadijeh, Lagree, Andrew, Alera, Marie A., Fleshner, Lauren, Shiner, Audrey, Law, Ethan, Law, Brianna, Dodington, David W., Lu, Fang-I, Tran, William T., Sadeghi-Naini, Ali
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9188550/
https://www.ncbi.nlm.nih.gov/pubmed/35690630
http://dx.doi.org/10.1038/s41598-022-13917-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9188550/
https://www.ncbi.nlm.nih.gov/pubmed/35690630
http://dx.doi.org/10.1038/s41598-022-13917-4

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