Deep learning prediction of pathological complete response, residual cancer burden, and progression-free survival in breast cancer patients

The goal of this study was to employ novel deep-learning convolutional-neural-network (CNN) to predict pathological complete response (PCR), residual cancer burden (RCB), and progression-free survival (PFS) in breast cancer patients treated with neoadjuvant chemotherapy using longitudinal multiparam...

Descripción completa

Detalles Bibliográficos
Autores principales: Dammu, Hongyi, Ren, Thomas, Duong, Tim Q.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9821469/
https://www.ncbi.nlm.nih.gov/pubmed/36607982
http://dx.doi.org/10.1371/journal.pone.0280148

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9821469/
https://www.ncbi.nlm.nih.gov/pubmed/36607982
http://dx.doi.org/10.1371/journal.pone.0280148

Ejemplares similares