CASIA OpenIR

浏览/检索结果: 共9条,第1-9条 帮助

限定条件        
已选(0)清除 条数/页:   排序方式:
Deep learning radiomics of dual-energy computed tomography for predicting lymph node metastases of pancreatic ductal adenocarcinoma 期刊论文
EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING, 2021, 页码: 13
作者:  An, Chao;  Li, Dongyang;  Li, Sheng;  Li, Wangzhong;  Tong, Tong;  Liu, Lizhi;  Jiang, Dongping;  Jiang, Linling;  Ruan, Guangying;  Hai, Ning;  Fu, Yan;  Wang, Kun;  Zhuo, Shuiqing;  Tian, Jie
Adobe PDF(2925Kb)  |  收藏  |  浏览/下载:304/58  |  提交时间:2021/12/28
Lymph node metastases  Pancreatic ductal adenocarcinoma  Deep learning  Dual-energy computed tomography  Prognosis  
Deep learning radiomics of ultrasonography can predict response to neoadjuvant chemotherapy in breast cancer at an early stage of treatment: a prospective study 期刊论文
EUROPEAN RADIOLOGY, 2021, 页码: 11
作者:  Gu, Jionghui;  Tong, Tong;  He, Chang;  Xu, Min;  Yang, Xin;  Tian, Jie;  Jiang, Tianan;  Wang, Kun
Adobe PDF(3007Kb)  |  收藏  |  浏览/下载:273/47  |  提交时间:2021/12/28
Breast cancer  Deep learning  Neoadjuvant chemotherapy  Ultrasonography  Treatment outcome  
Radiomics diagnosed histopathological growth pattern in prediction of response and 1-year progression free survival for colorectal liver metastases patients treated with bevacizumab containing chemotherapy 期刊论文
EUROPEAN JOURNAL OF RADIOLOGY, 2021, 卷号: 142, 页码: 8
作者:  Wei, Shengcai;  Han, Yuqi;  Zeng, Hanjiang;  Ye, Shuai;  Cheng, Jin;  Chai, Fan;  Wei, Jingwei;  Zhang, Jianwei;  Hong, Nan;  Bao, Yudi;  Zhou, Jing;  Ye, Yingjiang;  Meng, Xiaochun;  Zhou, Yuwen;  Deng, Yanhong;  Qiu, Meng;  Tian, Jie;  Wang, Yi
收藏  |  浏览/下载:258/0  |  提交时间:2021/11/03
Histopathologic growth pattern  Colorectal liver metastases  Unresectable  Radiomics  Bevacizumab  
Activable Nanoparticle for Tumor Aggressiveness and Drug Resistance Prediction by Glutathione Heterogeneous Imaging 期刊论文
JOURNAL OF BIOMEDICAL NANOTECHNOLOGY, 2021, 卷号: 17, 期号: 7, 页码: 1339-1348
作者:  Wang, Yaqin;  Shang, Wenting;  Xiong, Jianping;  Liu, Yu;  Luo, Ting;  Qi, Xun;  Niu, Meng;  Xu, Ke
收藏  |  浏览/下载:211/0  |  提交时间:2021/11/03
GSH imaging  Tumor Invasiveness  Resistance  Heterogenetic  Nanoparticle  Ratiometric Photoacoustic Imaging  
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:234/0  |  提交时间:2021/11/03
biochemical recurrence-free survival  gene signature  LASSO-Cox regression  primary prostate cancer  radical therapy  
Prediction of Microvascular Invasion in Hepatocellular Carcinoma via Deep Learning: A Multi-Center and Prospective Validation Study 期刊论文
CANCERS, 2021, 卷号: 13, 期号: 10, 页码: 19
作者:  Wei, Jingwei;  Jiang, Hanyu;  Zeng, Mengsu;  Wang, Meiyun;  Niu, Meng;  Gu, Dongsheng;  Chong, Huanhuan;  Zhang, Yanyan;  Fu, Fangfang;  Zhou, Mu;  Chen, Jie;  Lyv, Fudong;  Wei, Hong;  Bashir, Mustafa R.;  Song, Bin;  Li, Hongjun;  Tian, Jie
Adobe PDF(2568Kb)  |  收藏  |  浏览/下载:361/59  |  提交时间:2021/06/15
hepatocellular carcinoma  microvascular invasion  magnetic resonance imaging  computed tomography  deep learning  
Adaptive Grouping Block Sparse Bayesian Learning Method for Accurate and Robust Reconstruction in Bioluminescence Tomography 期刊论文
IEEE Transactions on Biomedical Engineering, 2021, 卷号: 68, 期号: 99, 页码: 1
作者:  Yin, Lin;  Wang, Kun;  Tong, Tong;  Wang, Qian;  An, Yu;  Yang, Xin;  Tian, Jie
Adobe PDF(11700Kb)  |  收藏  |  浏览/下载:257/47  |  提交时间:2021/05/31
adaptive grouping  bioluminescence tomography  block sparse Bayesian learning  
ImmunoAIzer: A Deep Learning-Based Computational Framework to Characterize Cell Distribution and Gene Mutation in Tumor Microenvironment 期刊论文
CANCERS, 2021, 卷号: 13, 期号: 7, 页码: 21
作者:  Bian, Chang;  Wang, Yu;  Lu, Zhihao;  An, Yu;  Wang, Hanfan;  Kong, Lingxin;  Du, Yang;  Tian, Jie
Adobe PDF(14076Kb)  |  收藏  |  浏览/下载:273/23  |  提交时间:2021/05/17
deep learning  cell distribution  biomarker  tumor gene mutation  tumor microenvironment (TME)  semi-supervised learning  hematoxylin and eosin (H&  E)  
Application of deep learning to predict underestimation in ductal carcinoma in situ of the breast with ultrasound 期刊论文
ANNALS OF TRANSLATIONAL MEDICINE, 2021, 卷号: 9, 期号: 4, 页码: 9
作者:  Qian, Lang;  Lv, Zhikun;  Zhang, Kai;  Wang, Kun;  Zhu, Qian;  Zhou, Shichong;  Chang, Cai;  Tian, Jie
Adobe PDF(743Kb)  |  收藏  |  浏览/下载:316/63  |  提交时间:2021/04/21
Artificial intelligence (AI)  ductal carcinoma in situ (DCIS)  core needle biopsy (CNB)  prediction of upstaging