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Computed tomography-based radiomic model at node level for the prediction of normal-sized lymph node metastasis in cervical cancer
期刊论文
TRANSLATIONAL ONCOLOGY, 2021, 卷号: 14, 期号: 8, 页码: 7
Authors:
Liu, Yujia
;
Fan, Huijian
;
Dong, Di
;
Liu, Ping
;
He, Bingxi
;
Meng, Lingwei
;
Chen, Jiaming
;
Chen, Chunlin
;
Lang, Jinghe
;
Tian, Jie
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View/Download:40/0
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Submit date:2021/11/03
Cervical cancer
Lymph node metastasis
Radiomics
Preoperative prediction
Classifiers
Multiparametric MRI-based radiomics analysis for the prediction of breast tumor regression patterns after neoadjuvant chemotherapy
期刊论文
TRANSLATIONAL ONCOLOGY, 2020, 卷号: 13, 期号: 11, 页码: 8
Authors:
Zhuang, Xiaosheng
;
Chen, Chi
;
Liu, Zhenyu
;
Zhang, Liulu
;
Zhou, Xuezhi
;
Cheng, Minyi
;
Ji, Fei
;
Zhu, Teng
;
Lei, Chuqian
;
Zhang, Junsheng
;
Jiang, Jingying
;
Tian, Jie
;
Wang, Kun
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View/Download:61/0
  |  
Submit date:2021/01/07
Building CT Radiomics-Based Models for Preoperatively Predicting Malignant Potential and Mitotic Count of Gastrointestinal Stromal Tumors
期刊论文
TRANSLATIONAL ONCOLOGY, 2019, 卷号: 12, 期号: 9, 页码: 1229-1236
Authors:
Wang, Chao
;
Li, Hailin
;
Jiaerken, Yeerfan
;
Huang, Peiyu
;
Sun, Lifeng
;
Dong, Fei
;
Huang, Yajing
;
Dong, Di
;
Tian, Jie
;
Zhang, Minming
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View/Download:91/0
  |  
Submit date:2019/12/16
Quantitative Biomarkers for Prediction of Epidermal Growth Factor Receptor Mutation in Non-Small Cell Lung Cancer
期刊论文
TRANSLATIONAL ONCOLOGY, 2018, 卷号: 11, 期号: 1, 页码: 94-101
Authors:
Zhang, Liwen
;
Chen, Bojiang
;
Liu, Xia
;
Song, Jiangdian
;
Fang, Mengjie
;
Hu, Chaoen
;
Dong, Di
;
Li, Weimin
;
Tian, Jie
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  |  
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View/Download:280/85
  |  
Submit date:2018/01/09
Radiomics
Diagnosis of Distant Metastasis of Lung Cancer: Based on Clinical and Radiomic Features
期刊论文
TRANSLATIONAL ONCOLOGY, 2018, 卷号: 11, 期号: 1, 页码: 31-36
Authors:
Zhou, Hongyu
;
Dong, Di
;
Chen, Bojiang
;
Fang, Mengjie
;
Cheng, Yue
;
Gan, Yuncun
;
Zhang, Rui
;
Zhang, Liwen
;
Zang, Yali
;
Liu, Zhenyu
;
Zheng, Hairong
;
Li, Weimin
;
Tian, Jie
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View/Download:214/31
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Submit date:2018/01/09
Radiomics