机构:[1]Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, No. 30 Shuangqing Road, Haidian District, Beijing 100084, China[2]Department of Minimal Invasive Intervention, Sun Yat-sen University Cancer Center, Guangzhou, China[3]Department of Minimal Invasive Intervention, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China[4]Department of Ultrasound, The Sixth Medical Center of Chinese PLA General Hospital, Beijing, China[5]Department of Minimal Invasive Intervention, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China中山大学附属第一医院[6]Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, No. 45, Changchun Street, Xicheng District, Beijing 100053, China医技科室放射科首都医科大学宣武医院
This study received funding from the Beijing Municipal Natural
Science Foundation (Z190024) and the Key Program of the National
Natural Science Foundation of China (81930119).
第一作者机构:[1]Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, No. 30 Shuangqing Road, Haidian District, Beijing 100084, China
共同第一作者:
通讯作者:
推荐引用方式(GB/T 7714):
Xu Ziming,An Chao,Shi Feng,et al.Automatic prediction of hepatic arterial infusion chemotherapy response in advanced hepatocellular carcinoma with deep learning radiomic nomogram[J].EUROPEAN RADIOLOGY.2023,33(12):9038-9051.doi:10.1007/s00330-023-09953-x.
APA:
Xu Ziming,An Chao,Shi Feng,Ren He,Li Yuze...&Chen Huijun.(2023).Automatic prediction of hepatic arterial infusion chemotherapy response in advanced hepatocellular carcinoma with deep learning radiomic nomogram.EUROPEAN RADIOLOGY,33,(12)
MLA:
Xu Ziming,et al."Automatic prediction of hepatic arterial infusion chemotherapy response in advanced hepatocellular carcinoma with deep learning radiomic nomogram".EUROPEAN RADIOLOGY 33..12(2023):9038-9051