Deep radiomics-based fusion model for prediction of bevacizumab treatment response and outcome in patients with colorectal cancer liver metastases: a multicentre cohort study

BACKGROUND: Accurate tumour response prediction to targeted therapy allows for personalised conversion therapy for patients with unresectable colorectal cancer liver metastases (CRLM). In this study, we aimed to develop and validate a multi-modal deep learning model to predict the efficacy of bevaci...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhou, Shizhao, Sun, Dazhen, Mao, Wujian, Liu, Yu, Cen, Wei, Ye, Lechi, Liang, Fei, Xu, Jianmin, Shi, Hongcheng, Ji, Yuan, Wang, Lisheng, Chang, Wenju
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10589780/
https://www.ncbi.nlm.nih.gov/pubmed/37869523
http://dx.doi.org/10.1016/j.eclinm.2023.102271

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10589780/
https://www.ncbi.nlm.nih.gov/pubmed/37869523
http://dx.doi.org/10.1016/j.eclinm.2023.102271

Ejemplares similares