https://www.selleckchem.com/pr....oducts/durvalumab.ht
76-0.78 and 0.79-0.84. The nomogram had powerful diagnostic ability in all training, test I and II sets with AUCs of 0.90 (95 % CI, 0.86-0.94), 0.87 (95 % CI, 0.82-0.92) and 0.90 (95 % CI, 0.85-0.96) respectively. The net reclassification index revealed that the radiomics nomogram had significantly better performance than the clinical model (p-values 0.05). The deep learning radiomics model based on CT images is effective at discriminating serosa invasion in gastric cancer. The deep learning radiomics model based on CT images is
Мне нравится
Комментарий
Перепост
