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A deep learning-based radiomic nomogram for prognosis and treatment decision in advanced nasopharyngeal carcinoma: A multicentre study 期刊论文
EBIOMEDICINE, 2021, 卷号: 70, 页码: 10
作者:  Zhong, Lianzhen;  Dong, Di;  Fang, Xueliang;  Zhang, Fan;  Zhang, Ning;  Zhang, Liwen;  Fang, Mengjie;  Jiang, Wei;  Liang, Shaobo;  Li, Cong;  Liu, Yujia;  Zhao, Xun;  Cao, Runnan;  Shan, Hong;  Hu, Zhenhua;  Ma, Jun;  Tang, Linglong;  Tian, Jie
Adobe PDF(3679Kb)  |  收藏  |  浏览/下载：426/78  |  提交时间：2021/11/03
Multi-task deep learning  Radiomic nomogram  Survival analysis  Treatment decision  Advanced nasopharyngeal carcinoma  
Classification of Severe and Critical Covid-19 Using Deep Learning and Radiomics 期刊论文
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2020, 卷号: 24, 期号: 12, 页码: 3585-3594
作者:  Li, Cong;  Dong, Di;  Li, Liang;  Gong, Wei;  Li, Xiaohu;  Bai, Yan;  Wang, Meiyun;  Hu, Zhenhua;  Zha, Yunfei;  Tian, Jie
Adobe PDF(2325Kb)  |  收藏  |  浏览/下载：445/67  |  提交时间：2021/03/02
COVID-19  radiomics  deep learning  computed tomography (CT)  
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：371/67  |  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  
Predicting the Type of Tumor-Related Epilepsy in Patients With Low-Grade Gliomas: A Radiomics Study 期刊论文
FRONTIERS IN ONCOLOGY, 2020, 卷号: 10, 页码: 8
作者:  Wang, Yinyan;  Wei, Wei;  Liu, Zhenyu;  Liang, Yuchao;  Liu, Xing;  Li, Yiming;  Tang, Zhenchao;  Jiang, Tao;  Tian, Jie
收藏  |  浏览/下载：291/0  |  提交时间：2020/06/02
epilepsy type  low-grade gliomas  machine learning  radiomics  T2-weighted imaging  
Multi-parametric MRI-based radiomics signature for discriminating between clinically significant and insignificant prostate cancer: Cross-validation of a machine learning method 期刊论文
EUROPEAN JOURNAL OF RADIOLOGY, 2019, 卷号: 115, 页码: 16-21
作者:  Min, Xiangde;  Li, Min;  Dong, Di;  Feng, Zhaoyan;  Zhang, Peipei;  Ke, Zan;  You, Huijuan;  Han, Fangfang;  Ma, He;  Tian, Jie;  Wang, Liang
收藏  |  浏览/下载：343/0  |  提交时间：2019/07/12
Magnetic resonance imaging  Prostatic neoplasms  Neoplasm grading  Radiomics