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...

Descripción completa

Detalles Bibliográficos
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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Research Article
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

Internet

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

Ejemplares similares