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Development and Validation of a Deep Learning Model to Screen for Trisomy 21 During the First Trimester From Nuchal Ultrasonographic Images 期刊论文
JAMA NETWORK OPEN, 2022, 卷号: 5, 期号: 6, 页码: 11
作者:  Zhang, Liwen;  Dong, Di;  Sun, Yongqing;  Hu, Chaoen;  Sun, Congxin;  Wu, Qingqing;  Tian, Jie
收藏  |  浏览/下载：229/0  |  提交时间：2022/07/25
Deep learning for predicting immunotherapeutic efficacy in advanced non-small cell lung cancer patients: a retrospective study combining progression-free survival risk and overall survival risk 期刊论文
TRANSLATIONAL LUNG CANCER RESEARCH, 2022, 页码: 23
作者:  He, Bing-Xi;  Zhong, Yi-Fan;  Zhu, Yong-Bei;  Deng, Jia-Jun;  Fang, Meng-Jie;  She, Yun-Lang;  Wang, Ting-Ting;  Yang, Yang;  Sun, Xi-Wen;  Belluomini, Lorenzo;  Watanabe, Satoshi;  Dong, Di;  Tian, Jie;  Xie, Dong
Adobe PDF(3742Kb)  |  收藏  |  浏览/下载：328/39  |  提交时间：2022/06/10
Tumor biomarkers  immunotherapy  lung neoplasms  programmed cell death 1 receptor (PD-1 receptor)  biostatistics  
Deep learning radiomics based on contrast-enhanced ultrasound images for assisted diagnosis of pancreatic ductal adenocarcinoma and chronic pancreatitis 期刊论文
BMC MEDICINE, 2022, 卷号: 20, 期号: 1, 页码: 15
作者:  Tong, Tong;  Gu, Jionghui;  Xu, Dong;  Song, Ling;  Zhao, Qiyu;  Cheng, Fang;  Yuan, Zhiqiang;  Tian, Shuyuan;  Yang, Xin;  Tian, Jie;  Wang, Kun;  Jiang, Tian'an
Adobe PDF(9703Kb)  |  收藏  |  浏览/下载：357/58  |  提交时间：2022/06/06
Deep learning  Artificial intelligence  Pancreatic ductal adenocarcinoma  Contrast-enhanced ultrasound  Chronic pancreatitis  
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：280/49  |  提交时间：2021/12/28
Breast cancer  Deep learning  Neoadjuvant chemotherapy  Ultrasonography  Treatment outcome  
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：369/61  |  提交时间：2021/06/15
hepatocellular carcinoma  microvascular invasion  magnetic resonance imaging  computed tomography  deep learning  
Comparing radiomics models with different inputs for accurate diagnosis of significant fibrosis in chronic liver disease 期刊论文
EUROPEAN RADIOLOGY, 2021, 页码: 12
作者:  Lu, Xue;  Zhou, Hui;  Wang, Kun;  Jin, Jieyang;  Meng, Fankun;  Mu, Xiaojie;  Li, Shuoyang;  Zheng, Rongqin;  Tian, Jie
收藏  |  浏览/下载：270/0  |  提交时间：2021/06/07
Liver disease  Hepatic cirrhosis  Elasticity imaging techniques  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：262/48  |  提交时间：2021/05/31
adaptive grouping  bioluminescence tomography  block sparse Bayesian learning  
Exploring the predictive value of additional peritumoral regions based on deep learning and radiomics: A multicenter study 期刊论文
MEDICAL PHYSICS, 2021, 页码: 12
作者:  Wu, Xiangjun;  Dong, Di;  Zhang, Lu;  Fang, Mengjie;  Zhu, Yongbei;  He, Bingxi;  Ye, Zhaoxiang;  Zhang, Minming;  Zhang, Shuixing;  Tian, Jie
Adobe PDF(3862Kb)  |  收藏  |  浏览/下载：683/360  |  提交时间：2021/05/06
deep learning  peritumor  radiomics  
Deep learning-based radiomics predicts response to chemotherapy in colorectal liver metastases 期刊论文
MEDICAL PHYSICS, 2020, 页码: 10
作者:  Wei, Jingwei;  Cheng, Jin;  Gu, Dongsheng;  Chai, Fan;  Hong, Nan;  Wang, Yi;  Tian, Jie
收藏  |  浏览/下载：227/0  |  提交时间：2021/01/06
colorectal liver metastases  chemotherapy  radiomics  contrast‐  enhanced multidetector computed tomography  deep learning  
Cascaded one-shot deformable convolutional neural networks: Developing a deep learning model for respiratory motion estimation in ultrasound sequences 期刊论文
Medical Image Analysis, 2020, 卷号: 65, 期号: 65, 页码: 101793
作者:  Fei Liu;  Dan Liu;  Jie Tian;  Xiaoyan Xie;  Xin Yang;  Wang K(王坤)
浏览  |  Adobe PDF(3180Kb)  |  收藏  |  浏览/下载：200/56  |  提交时间：2020/11/02
Ultrasound sequence  Respiratory motion estimation  Cascaded Siamese network  One-shot deformable convolution