Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Su-E Cao"'
Publikováno v:
Clinical Nuclear Medicine; Sep2024, Vol. 49 Issue 9, pe457-e458, 2p
Autor:
Yinan Deng, Guoying Wang, Kaining Zeng, Na Cheng, Xi-Jing Yan, Yi-Quan Jiang, Wei-Min Tang, Jian-ning Chen, Wen-Jing Huan, Wen-Qi Shi, Gui-hua Chen, Yang Yang, Kai Ma, Yefeng Zheng, Shilei Cao, Yang Haozhen, Chun-Kui Shao, Su-E Cao, Jin Wang
Publikováno v:
Journal of Cancer Research and Clinical Oncology
Purpose Microvascular invasion (MVI) is a valuable predictor of survival in hepatocellular carcinoma (HCC) patients. This study developed predictive models using eXtreme Gradient Boosting (XGBoost) and deep learning based on CT images to predict MVI
Autor:
Bing Hu, Chen Yunqiang, Chen Yinan, Jin Wang, Sidong Xie, Sichi Kuang, Wen-Qi Shi, Han-Xi Zhang, Dashan Gao, Meng Ye, Hui Liu, Zhu Yajing, Simin Chen, Su-E Cao, Claude B. Sirlin
Publikováno v:
Abdominal Radiology. 45:2688-2697
To evaluate whether a three-phase dynamic contrast-enhanced CT protocol, when combined with a deep learning model, has similar accuracy in differentiating hepatocellular carcinoma (HCC) from other focal liver lesions (FLLs) compared with a four-phase
Autor:
Su-E Cao, Sidong Xie, Hui Liu, Sichi Kuang, Han-Xi Zhang, Jin Wang, Bing Hu, Ting Jiang, Simin Chen, Meng Ye, Linqi Zhang, Wen-Qi Shi, Chen Yinan
Publikováno v:
World Journal of Gastroenterology
Background The accurate classification of focal liver lesions (FLLs) is essential to properly guide treatment options and predict prognosis. Dynamic contrast-enhanced computed tomography (DCE-CT) is still the cornerstone in the exact classification o