Machine learning assisted radiomics in predicting postoperative occurrence of deep venous thrombosis in patients with gastric cancer.
Journal:
BMC cancer
PMID:
39920636
Abstract
BACKGROUND: Gastric cancer patients are prone to lower extremity deep vein thrombosis (DVT) after surgery, which is an important cause of death in postoperative patients. Therefore, it is particularly important to find a suitable way to predict the risk of postoperative occurrence of DVT in GC patients. This study aims to explore the effectiveness of using machine learning (ML) assisted radiomics to build imaging models for prediction of lower extremity DVT occurrence in GC patients after surgery.