Research progress in radiomics and deep learning for early prediction and efficacy evaluation in colorectal cancer liver metastases / 中国肿瘤临床
Chinese Journal of Clinical Oncology
; (24): 36-40, 2024.
Article
in Zh
| WPRIM
| ID: wpr-1026750
Responsible library:
WPRO
ABSTRACT
Radiomics-based early prediction and treatment efficacy evaluation is critical for personalized treatment strategies in patients with colorectal cancer liver metastases(CCLM).Owing to the high artificial intelligence(AI)participation,repeatability,and reliable perform-ance,deep learning(DL)based on convolutional neural networks enhances the predictive efficacy of the models,enabling its potential clinic-al application more promising.Subsequent to the gradual construction of a multimodal fusion model and multicenter large sample database,radiomics and DL will become increasingly essential in the management of CCLM.This review focuses on the main steps of radiomics and DL,and summarizes the value of its application in early state prediction and treatment efficacy evaluation of different treatment modalities in CCLM,we also look forward to the potential of its in-depth application in the clinical management of CCLM.
Full text:
1
Index:
WPRIM
Language:
Zh
Journal:
Chinese Journal of Clinical Oncology
Year:
2024
Type:
Article