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

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

Summary: 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...

Full description

Bibliographic Details
Main Authors: Shizhao Zhou, Dazhen Sun, Wujian Mao, Yu Liu, Wei Cen, Lechi Ye, Fei Liang, Jianmin Xu, Hongcheng Shi, Yuan Ji, Lisheng Wang, Wenju Chang
Format: Article
Language:English
Published: Elsevier 2023-11-01
Series:EClinicalMedicine
Subjects:
Colorectal cancer
Liver metastases
Multi-modal
Deep learning
Treatment efficacy
Online Access:http://www.sciencedirect.com/science/article/pii/S2589537023004480

Internet

http://www.sciencedirect.com/science/article/pii/S2589537023004480

Similar Items