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Machine Learning Predicts Pathologic Complete Response to Neoadjuvant Chemotherapy for ER+HER2- Breast Cancer: Integrating Tumoral and Peritumoral MRI Radiomic Features
Background: This study aimed to predict pathologic complete response (pCR) in neoadjuvant chemotherapy for ER+HER2- locally advanced breast cancer (LABC), a subtype with limited treatment response. Methods: We included 265 ER+HER2- LABC patients (2010–2020) with pre-treatment MRI, neoadjuvant chemot...
Autores principales: | Park, Jiwoo, Kim, Min Jung, Yoon, Jong-Hyun, Han, Kyunghwa, Kim, Eun-Kyung, Sohn, Joo Hyuk, Lee, Young Han, Yoo, Yangmo |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10572844/ https://www.ncbi.nlm.nih.gov/pubmed/37835774 http://dx.doi.org/10.3390/diagnostics13193031 |
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