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...

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Detalles Bibliográficos
Autores principales: Park, Jiwoo, Kim, Min Jung, Yoon, Jong-Hyun, Han, Kyunghwa, Kim, Eun-Kyung, Sohn, Joo Hyuk, Lee, Young Han, Yoo, Yangmo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
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

Internet

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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