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Assessing PD-L1 expression in non-small cell lung cancer and predicting responses to immune checkpoint inhibitors using deep learning on computed tomography images 期刊论文
Theranostics, 2020, 卷号: 0, 期号: 0, 页码: 0
作者:  Tian, Panwen;  He, Bingxi;  Dong, Di;  Mu, Wei;  Liu, Kunqin;  Liu, Li;  Zeng, Hao;  Liu, Yujie;  Jiang, Lili;  Zhou, Ping;  Huang, Zhipei;  Li, Weimin;  Tian, Jie
浏览  |  Adobe PDF(1539Kb)  |  收藏  |  浏览/下载：284/114  |  提交时间：2020/10/25
PD-L1 expression  deep learning  computed tomography  immunotherapy  non-small cell lung 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：341/56  |  提交时间：2020/08/24
immunotherapy  lung neoplasms  tumor microenvironment  biomarkers  tumor  biostatistics  
Multi-Habitat Based Radiomics for the Prediction of Treatment Response to Concurrent Chemotherapy and Radiation Therapy in Locally Advanced Cervical Cancer 期刊论文
FRONTIERS IN ONCOLOGY, 2020, 卷号: 10, 页码: 8
作者:  Fang, Mengjie;  Kan, Yangyang;  Dong, Di;  Yu, Tao;  Zhao, Nannan;  Jiang, Wenyan;  Zhong, Lianzhen;  Hu, Chaoen;  Luo, Yahong;  Tian, Jie
Adobe PDF(730Kb)  |  收藏  |  浏览/下载：340/54  |  提交时间：2020/06/22
cervical cancer  MRI  radiomics  treatment response prediction  concurrent chemotherapy and radiation therapy  precision medicine  
Computed Tomography Radiomic Nomogram for Preoperative Prediction of Extrathyroidal Extension in Papillary Thyroid Carcinoma 期刊论文
FRONTIERS IN ONCOLOGY, 2019, 卷号: 9, 页码: 9
作者:  Chen, Bin;  Zhong, Lianzhen;  Dong, Di;  Zheng, Jianjun;  Fang, Mengjie;  Yu, Chunyao;  Dai, Qi;  Zhang, Liwen;  Tian, Jie;  Lu, Wei;  Jin, Yinhua
Adobe PDF(1219Kb)  |  收藏  |  浏览/下载：331/54  |  提交时间：2019/12/16
thyroid cancer  computed tomography  radiomics  tumor staging  nomograms