中文版 | English

在结果中检索

CASIA OpenIR

浏览/检索结果: 共14条，第1-10条 帮助

限定条件                    
已选(0)清除 条数/页：   排序方式：
A Deep Learning Prognosis Model Help Alert for COVID-19 Patients at High-Risk of Death: A Multi-Center Study 期刊论文
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2020, 卷号: 24, 期号: 12, 页码: 3576-3584
作者:  Meng, Lingwei;  Dong, Di;  Li, Liang;  Niu, Meng;  Bai, Yan;  Wang, Meiyun;  Qiu, Xiaoming;  Zha, Yunfei;  Tian, Jie
Adobe PDF(4120Kb)  |  收藏  |  浏览/下载：323/54  |  提交时间：2021/03/02
COVID-19  Computed tomography  Lung  Hospitals  Biomedical imaging  Training  Coronavirus disease 2019 (COVID-19)  prognosis  computed tomography  deep learning  artificial intelligence  
A deep learning MR-based radiomic nomogram may predict survival for nasopharyngeal carcinoma patients with stage T3N1M0 期刊论文
Radiotherapy and Oncology, 2020, 卷号: 151, 期号: 1, 页码: 1-9
作者:  Zhong, Lianzhen;  Fang, Xueliang;  Dong, Di;  Peng, Hao;  Fang, Mengjie;  Huang, Chenglong;  He, Bingxi;  Lin, Li;  Ma, Jun;  Tang, Linglong;  Tian, Jie
浏览  |  Adobe PDF(8171Kb)  |  收藏  |  浏览/下载：187/75  |  提交时间：2020/10/25
nasopharyngeal carcinoma  
A Deep Learning Risk Prediction Model for Overall Survival in Patients with Gastric Cancer: A Multicenter Study 期刊论文
Radiotherapy and oncology, 2020, 卷号: 150, 期号: 1, 页码: 73-80
作者:  Zhang, Liwen;  Dong, Di;  Zhang, Wenjuan;  Hao, Xiaohan;  Fang, Mengjie;  Wang, Shuo;  Li, Wuchao;  Liu, Zaiyi;  Wang, Rongpin;  Zhou, Junlin;  Tian, Jie
浏览  |  Adobe PDF(1185Kb)  |  收藏  |  浏览/下载：262/63  |  提交时间：2020/10/25
Gastric Cancer  
Predicting response to immunotherapy in advanced non-small-cell lung cancer using tumor mutational burden radiomic biomarker 期刊论文
JOURNAL FOR IMMUNOTHERAPY OF CANCER, 2020, 卷号: 8, 期号: 2, 页码: 10
作者:  He, Bingxi;  Dong, Di;  She, Yunlang;  Zhou, Caicun;  Fang, Mengjie;  Zhu, Yongbei;  Zhang, Henghui;  Huang, Zhipei;  Jiang, Tao;  Tian, Jie;  Chen, Chang
浏览  |  Adobe PDF(5232Kb)  |  收藏  |  浏览/下载：344/57  |  提交时间：2020/08/24
immunotherapy  lung neoplasms  tumor microenvironment  biomarkers  tumor  biostatistics  
Radiomics in liver diseases: Current progress and future opportunities 期刊论文
LIVER INTERNATIONAL, 2020, 卷号: 40, 期号: 9, 页码: 2050-2063
作者:  Wei, Jingwei;  Jiang, Hanyu;  Gu, Dongsheng;  Niu, Meng;  Fu, Fangfang;  Han, Yuqi;  Song, Bin;  Tian, Jie
Adobe PDF(872Kb)  |  收藏  |  浏览/下载：469/130  |  提交时间：2020/08/03
data science  liver diseases  machine learning  precision medicine  radiologic technology  
Deep Learning for Virtual Histological Staining of Bright-Field Microscopic Images of Unlabeled Carotid Artery Tissue 期刊论文
MOLECULAR IMAGING AND BIOLOGY, 2020, 期号: 22, 页码: 1301-1309
作者:  Li, Dan;  Hui, Hui;  Zhang, Yingqian;  Tong, Wei;  Tian, Feng;  Yang, Xin;  Liu, Jie;  Chen, Yundai;  Tian, Jie
浏览  |  Adobe PDF(4159Kb)  |  收藏  |  浏览/下载：270/64  |  提交时间：2020/07/20
Virtual histological staining  Conditional generative adversarial network  Blind evaluation  Bright-field microscopic imaging  
MRI-Based Radiomics Signature: A Potential Biomarker for Identifying Glypican 3-Positive Hepatocellular Carcinoma 期刊论文
JOURNAL OF MAGNETIC RESONANCE IMAGING, 2020, 卷号: 52, 期号: 6, 页码: 1679-1687
作者:  Gu, Dongsheng;  Xie, Yongsheng;  Wei, Jingwei;  Li, Wencui;  Ye, Zhaoxiang;  Zhu, Zhongyuan;  Tian, Jie;  Li, Xubin
Adobe PDF(904Kb)  |  收藏  |  浏览/下载：236/38  |  提交时间：2020/07/20
glypican 3  hepatocellular carcinoma  radiomics  noninvasive  nomogram  
The improved reconstruction of fluorescence molecular tomography via regularized doubly orthogonal matching pursuit method 会议论文
, Houston, USA, 2020-2-16
作者:  Lingxin Kong;  Yu An;  Yang Du;  Jie Tian
Adobe PDF(1305Kb)  |  收藏  |  浏览/下载：262/63  |  提交时间：2020/06/15
Reconstruction for Fluorescence Molecular Tomography via Adaptive Group Orthogonal Matching Pursuit 期刊论文
IEEE Transactions on Biomedical Engineering, 2020, 卷号: 67, 期号: 10.1109/TBME.2019.2963815, 页码: 1-12
作者:  Kong, Lingxin;  An, Yu;  Liang, Qian;  Yin, Lin;  Du, Yang;  Tian, Jie
Adobe PDF(4495Kb)  |  收藏  |  浏览/下载：282/85  |  提交时间：2020/06/03
adaptive group orthogonal matching pursuit  fluorescence molecular tomography  local spatial structured sparsity regularization  inverse problem  
基于结构相关正交匹配追踪的激发荧光肝肿瘤重建研究 学位论文
, 自动化研究所: 中国科学院大学, 2020
作者:  孔令鑫
Adobe PDF(2986Kb)  |  收藏  |  浏览/下载：276/6  |  提交时间：2020/06/03
激发荧光断层成像  匹配追踪  组稀疏  斯密特正交化