https://www.selleckchem.com/products/gw6471.html
For patients with thymic epithelial tumors, accurately predicting clinicopathological outcomes remains challenging. We aimed to investigate the performance of machine learning-based radiomic computed tomography phenotyping for predicting pathological (World Health Organization [WHO] type and TNM stage) and survival outcomes (overall and progression-free survival) in patients with thymic epithelial tumors. This retrospective study included patients with thymic epithelial tumors between January 2001 and January 2022. The radiomic features
Mi piace
Commento
Condividi
