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A machine learning model that classifies breast cancer pathologic complete response on MRI post-neoadjuvant chemotherapy
BACKGROUND: For breast cancer patients undergoing neoadjuvant chemotherapy (NAC), pathologic complete response (pCR; no invasive or in situ) cannot be assessed non-invasively so all patients undergo surgery. The aim of our study was to develop and validate a radiomics classifier that classifies brea...
Autores principales: | Sutton, Elizabeth J., Onishi, Natsuko, Fehr, Duc A., Dashevsky, Brittany Z., Sadinski, Meredith, Pinker, Katja, Martinez, Danny F., Brogi, Edi, Braunstein, Lior, Razavi, Pedram, El-Tamer, Mahmoud, Sacchini, Virgilio, Deasy, Joseph O., Morris, Elizabeth A., Veeraraghavan, Harini |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7254668/ https://www.ncbi.nlm.nih.gov/pubmed/32466777 http://dx.doi.org/10.1186/s13058-020-01291-w |
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