中文版 | English

在结果中检索

CASIA OpenIR

浏览/检索结果: 共7条，第1-7条 帮助

限定条件    
已选(0)清除 条数/页：   排序方式：
Multi-Focus Network to Decode Imaging Phenotype for Overall Survival Prediction of Gastric Cancer Patients 期刊论文
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2021, 卷号: 25, 期号: 10, 页码: 3933-3942
作者:  Zhang, Liwen;  Dong, Di;  Zhong, Lianzhen;  Li, Cong;  Hu, Chaoen;  Yang, Xin;  Liu, Zaiyi;  Wang, Rongpin;  Zhou, Junlin;  Tian, Jie
收藏  |  浏览/下载：227/0  |  提交时间：2021/12/28
Hazards  Feature extraction  Computed tomography  Cancer  Radiomics  Indexes  Bioinformatics  Overall survival  gastric cancer  multi-level  CT image  deep learning  
Gene signatures predict biochemical recurrence-free survival in primary prostate cancer patients after radical therapy 期刊论文
CANCER MEDICINE, 2021, 页码: 11
作者:  Su, Qiang;  Liu, Zhenyu;  Chen, Chi;  Gao, Han;  Zhu, Yongbei;  Wang, Liusu;  Pan, Meiqing;  Liu, Jiangang;  Yang, Xin;  Tian, Jie
收藏  |  浏览/下载：212/0  |  提交时间：2021/11/03
biochemical recurrence-free survival  gene signature  LASSO-Cox regression  primary prostate cancer  radical therapy  
Deep learning radiomic nomogram can predict the number of lymph node metastasis in locally advanced gastric cancer: an international multicenter study 期刊论文
ANNALS OF ONCOLOGY, 2020, 卷号: 31, 期号: 7, 页码: 912-920
作者:  Dong, Di;  Fang, Mengjie;  Tang, Lei;  Shan, Xiuhong;  Gao, Jianbo;  Giganti, Francesco;  Wang, Rongpin;  Chen, Xin;  Wang, Xiaoxiao;  Palumbo, Diego;  Fu, Jia;  Li, Wuchao;  Li, Jing;  Zhong, Lianzhen;  De Cobelli, Francesco;  Ji, Jiafu;  Liu, Zaiyi;  Tian, Jie
浏览  |  Adobe PDF(2209Kb)  |  收藏  |  浏览/下载：368/62  |  提交时间：2020/07/20
deep learning  locally advanced gastric cancer  lymph node metastasis  radiomic nomogram  
2D and 3D CT Radiomic Features Performance Comparison in Characterization of Gastric Cancer: A Multi-center Study 期刊论文
IEEE Journal of Biomedical and Health Informatics, 2020, 卷号: 25, 期号: 3, 页码: 755-762
作者:  Meng, Lingwei;  Dong, Di;  Chen, Xin;  Fang, Mengjie;  Wang, Rongpin;  Li, Jing;  Liu, Zaiyi;  Tian, Jie
Adobe PDF(3010Kb)  |  收藏  |  浏览/下载：250/58  |  提交时间：2020/10/25
Computed tomography (CT)  
A Non-invasive Radiomic Method Using F-18-FDG PET Predicts Isocitrate Dehydrogenase Genotype and Prognosis in Patients With Glioma 期刊论文
FRONTIERS IN ONCOLOGY, 2019, 卷号: 9, 页码: 11
作者:  Li, Longfei;  Mu, Wei;  Wang, Yaning;  Liu, Zhenyu;  Liu, Zehua;  Wang, Yu;  Ma, Wenbin;  Kong, Ziren;  Wang, Shuo;  Zhou, Xuezhi;  Wei, Wei;  Cheng, Xin;  Lin, Yusong;  Tian, Jie
收藏  |  浏览/下载：281/0  |  提交时间：2020/03/30
F-18-FDG PET  radiomics  glioma  isocitrate dehydrogenase  non-invasive prediction  
Radiomic analysis for pretreatment prediction of response to neoadjuvant chemotherapy in locally advanced cervical cancer: A multicentre study 期刊论文
EBIOMEDICINE, 2019, 卷号: 46, 页码: 160-169
作者:  Sun, Caixia;  Tian, Xin;  Liu, Zhenyu;  Li, Weili;  Li, Pengfei;  Chen, Jiaming;  Zhang, Weifeng;  Fang, Ziyu;  Du, Peiyan;  Duan, Hui;  Liu, Ping;  Wang, Lihui;  Chen, Chunlin;  Tian, Jie
收藏  |  浏览/下载：282/0  |  提交时间：2019/12/16
Radiomics  Magnetic resonance imaging  Neoadjuvant chemotherapy  Locally advanced cervical cancer  
The diagnostic value of high-frequency power-based diffusion-weighted imaging in prediction of neuroepithelial tumour grading 期刊论文
EUROPEAN RADIOLOGY, 2017, 卷号: 27, 期号: 12, 页码: 5056-5063
作者:  Chen, Zhiye;  Zhou, Peng;  Lv, Bin;  Liu, Mengqi;  Wang, Yan;  Wang, Yulin;  Lou, Xin;  Gui, Qiuping;  He, Huiguang;  Ma, Lin
收藏  |  浏览/下载：278/0  |  提交时间：2018/03/03
Diffusion-weighted Imaging  High-frequency Power  Minimum Apparent Diffusion Coefficient  Neuroepithelial Tumour Grading  Magnetic Resonance Imaging