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DEEP LEARNING RADIOMICS FOR PREOPERATIVE PREDICTION OF MICROVASCULAR INVASION IN HEPATOCELLULAR CARCINOMA: A MULTICENTER AND PROSPECTIVE VALIDATION STUDY 期刊论文
HEPATOLOGY, 2020, 卷号: 72, 页码: 677A-678A
Authors:  Wei, Jingwei;  Jiang, Hanyu;  Gu, Dongsheng;  Zeng, Mengsu;  Wang, Meiyun;  Song, Bin;  Tian, Jie
Favorite  |  View/Download:2/0  |  Submit date:2021/01/07
Preoperative Prediction of Ancillary Lymph Node Metastasis in Breast Carcinoma Using Radiomics Features Based on the Fat-Suppressed T2 Sequence 期刊论文
ACADEMIC RADIOLOGY, 2020, 卷号: 27, 期号: 9, 页码: 1217-1225
Authors:  Tan, Hongna;  Gan, Fuwen;  Wu, Yaping;  Zhou, Jing;  Tian, Jie;  Lin, Yusong;  Wang, Meiyun
Favorite  |  View/Download:21/0  |  Submit date:2020/12/04
Breast cancer  Axillary lymph node  Metastasis  MRI  Radiomics  
Predicting distant metastasis and chemotherapy benefit in locally advanced rectal cancer 期刊论文
NATURE COMMUNICATIONS, 2020, 卷号: 11, 期号: 1, 页码: 11
Authors:  Liu, Zhenyu;  Meng, Xiaochun;  Zhang, Hongmei;  Li, Zhenhui;  Liu, Jiangang;  Sun, Kai;  Meng, Yankai;  Dai, Weixing;  Xie, Peiyi;  Ding, Yingying;  Wang, Meiyun;  Cai, Guoxiang;  Tian, Jie
Favorite  |  View/Download:2/0  |  Submit date:2021/01/07
A fully automatic deep learning system for COVID-19 diagnostic and prognostic analysis 期刊论文
EUROPEAN RESPIRATORY JOURNAL, 2020, 卷号: 56, 期号: 2, 页码: 11
Authors:  Wang, Shuo;  Zha, Yunfei;  Li, Weimin;  Wu, Qingxia;  Li, Xiaohu;  Niu, Meng;  Wang, Meiyun;  Qiu, Xiaoming;  Li, Hongjun;  Yu, He;  Gong, Wei;  Bai, Yan;  Li, Li;  Zhu, Yongbei;  Wang, Liusu;  Tian, Jie
Favorite  |  View/Download:23/0  |  Submit date:2020/09/21
Development of a Deep Learning Model to Identify Lymph Node Metastasis on Magnetic Resonance Imaging in Patients With Cervical Cancer 期刊论文
JAMA NETWORK OPEN, 2020, 卷号: 3, 期号: 7, 页码: 13
Authors:  Wu, Qingxia;  Wang, Shuo;  Zhang, Shuixing;  Wang, Meiyun;  Ding, Yingying;  Fang, Jin;  Qian, Wei;  Liu, Zhenyu;  Sun, Kai;  Jin, Yan;  Ma, He;  Tian, Jie
Favorite  |  View/Download:12/0  |  Submit date:2020/09/07
Radiomics analysis of placenta on T2WI facilitates prediction of postpartum haemorrhage: A multicentre study (vol 50, pg 355, 2019) 期刊论文
EBIOMEDICINE, 2020, 卷号: 55, 页码: 1
Authors:  Wu, Qingxia;  Yao, Kuan;  Liu, Zhenyu;  Li, Longfei;  Zhao, Xin;  Wang, Shuo;  Shang, Honglei;  Lin, Yusong;  Wen, Zejun;  Zhang, Xiaoan;  Tian, Jie;  Wang, Meiyun
Favorite  |  View/Download:13/0  |  Submit date:2020/06/22
Mammography-based radiomics nomogram: a potential biomarker to predict axillary lymph node metastasis in breast cancer 期刊论文
BRITISH JOURNAL OF RADIOLOGY, 2020, 卷号: 93, 期号: 1111, 页码: 11
Authors:  Tan, Hongna;  Wu, Yaping;  Bao, Fengchang;  Zhou, Jing;  Wan, Jianzhong;  Tian, Jie;  Lin, Yusong;  Wang, Meiyun
Favorite  |  View/Download:10/0  |  Submit date:2020/08/03
Radiomics Analysis of Computed Tomography helps predict poor prognostic outcome in COVID-19 期刊论文
THERANOSTICS, 2020, 卷号: 10, 期号: 16, 页码: 7231-7244
Authors:  Wu, Qingxia;  Wang, Shuo;  Liang, Li;  Wu, Qingxia;  Qian, Wei;  Hu, Yahua;  Li, Li;  Zhou, Xuezhi;  Ma, He;  Li, Hongjun;  Wang, Meiyun;  Qiu, Xiaoming;  Zha, Yunfei;  Tian, Jie
Favorite  |  View/Download:14/0  |  Submit date:2020/08/03
COVID-19  Computed tomography  Radiomics  Prognosis  Poor outcome  
Radiomics analysis of placenta on T2WI facilitates prediction of postpartum haemorrhage: A multicentre study 期刊论文
EBIOMEDICINE, 2019, 卷号: 50, 页码: 355-365
Authors:  Wu, Qingxia;  Yao, Kuan;  Liu, Zhenyu;  Li, Longfei;  Zhao, Xin;  Wang, Shuo;  Shang, Honglei;  Lin, Yusong;  Wen, Zejun;  Tian, Jie;  Wang, Meiyun
Favorite  |  View/Download:29/0  |  Submit date:2020/03/30
Radiomics  Placenta accreta spectrum  Postpartum haemorrhage  Estimated blood loss  Magnetic resonance imaging  
Radiomics analysis of magnetic resonance imaging improves diagnostic performance of lymph node metastasis in patients with cervical cancer 期刊论文
RADIOTHERAPY AND ONCOLOGY, 2019, 卷号: 138, 页码: 141-148
Authors:  Wu, Qingxia;  Wang, Shuo;  Chen, Xi;  Wang, Yan;  Dong, Li;  Liu, Zhenyu;  Tian, Jie;  Wang, Meiyun
Favorite  |  View/Download:68/0  |  Submit date:2019/12/16
Radiomics  Cervical cancer  Lymph nodes  Magnetic resonance imaging