Machine Learning Models and Multiparametric Magnetic Resonance Imaging for the Prediction of Pathologic Response to Neoadjuvant Chemotherapy in Breast Cancer

SIMPLE SUMMARY: Achieving pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer (BC) is crucial, as pCR is a surrogate marker for survival. However, only 10–30% of patients achieve it. It is therefore essential to develop tools that enable to accurately predict resp...

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Detalles Bibliográficos
Autores principales: Herrero Vicent, Carmen, Tudela, Xavier, Moreno Ruiz, Paula, Pedralva, Víctor, Jiménez Pastor, Ana, Ahicart, Daniel, Rubio Novella, Silvia, Meneu, Isabel, Montes Albuixech, Ángela, Santamaria, Miguel Ángel, Fonfria, María, Fuster-Matanzo, Almudena, Olmos Antón, Santiago, Martínez de Dueñas, Eduardo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9317428/
https://www.ncbi.nlm.nih.gov/pubmed/35884572
http://dx.doi.org/10.3390/cancers14143508

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9317428/
https://www.ncbi.nlm.nih.gov/pubmed/35884572
http://dx.doi.org/10.3390/cancers14143508

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