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Intratumoral and peritumoral radiomics analysis for preoperative Lauren classification in gastric cancer 期刊论文
CANCER IMAGING, 2020, 卷号: 20, 期号: 1, 页码: 10
Authors:  Wang, Xiao-Xiao;  Ding, Yi;  Wang, Si-Wen;  Dong, Di;  Li, Hai-Lin;  Chen, Jian;  Hu, Hui;  Lu, Chao;  Tian, Jie;  Shan, Xiu-Hong
Favorite  |  View/Download：4/0  |  Submit date：2021/01/06
Lauren classification  Radiomics  Peritumoral analysis  Gastric cancer  Computed tomography  
CT-based deep learning radiomics analysis for evaluation of serosa invasion in advanced gastric cancer 期刊论文
EUROPEAN JOURNAL OF RADIOLOGY, 2020, 卷号: 132, 页码: 8
Authors:  Sun, Rui-Jia;  Fang, Meng-Jie;  Tang, Lei;  Li, Xiao-Ting;  Lu, Qiao-Yuan;  Dong, Di;  Tian, Jie;  Sun, Ying-Shi
Favorite  |  View/Download：4/0  |  Submit date：2021/01/06
Stomach neoplasms  Multi-detector computed tomography  Radiomics  Deep learning  
Preoperative computed tomography-guided disease-free survival prediction in gastric cancer: a multicenter radiomics study 期刊论文
MEDICAL PHYSICS, 2020, 页码: 10
Authors:  Wang, Siwen;  Feng, Caizhen;  Dong, Di;  Li, Hailin;  Zhou, Jing;  Ye, Yingjiang;  Liu, Zaiyi;  Tian, Jie;  Wang, Yi
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disease-free survival  gastric cancer  multidetector-row computed tomography  risk stratification  radiomics  
Deep learning radiomic nomogram can predict the number of lymph node metastasis in locally advanced gastric cancer: an international multicenter study 期刊论文
ANNALS OF ONCOLOGY, 2020, 卷号: 31, 期号: 7, 页码: 912-920
Authors:  Dong, D.;  Fang, M. -J.;  Tang, L.;  Shan, X. -H.;  Gao, J. -B.;  Giganti, F.;  Wang, R. -P.;  Chen, X.;  Wang, X. -X.;  Palumbo, D.;  Fu, J.;  Li, W. -C.;  Li, J.;  Zhong, L. -Z.;  De Cobelli, F.;  Ji, J. -F.;  Liu, Z. -Y.;  Tian, J.
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Deep learning radiomic nomogram can predict the number of lymph node metastasis in locally advanced gastric cancer: an international multicenter study 期刊论文
ANNALS OF ONCOLOGY, 2020, 卷号: 31, 期号: 7, 页码: 912-920
Authors:  Dong, Di;  Fang, Mengjie;  Tang, Lei;  Shan, Xiuhong;  Gao, Jianbo;  Giganti, Francesco;  Wang, Rongpin;  Chen, Xin;  Wang, Xiaoxiao;  Palumbo, Diego;  Fu, Jia;  Li, Wuchao;  Li, Jing;  Zhong, Lianzhen;  De Cobelli, Francesco;  Ji, Jiafu;  Liu, Zaiyi;  Tian, Jie
View  |  Adobe PDF(2209Kb)  |  Favorite  |  View/Download：33/5  |  Submit date：2020/07/20
deep learning  locally advanced gastric cancer  lymph node metastasis  radiomic nomogram  
Computational Bioinformatics and Machine Learning Models to Identify the Diseasome and Neurological Disease Comorbidities 学位论文
, 中国科学院自动化研究所: 中国科学院大学, 2020
Authors:  Md Habibur Rahman
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疾病共病鉴定  生存分析  生物信息学  机器学习  2 型糖尿病  神经系统疾病  胶质母细胞瘤  通路  基因本体  蛋白质  
基于深度学习策略的超声多模态影像组学方法研究 学位论文
, 中国科学院大学自动化研究所: 中国科学院大学, 2020
Authors:  周辉
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超声成像  深度学习  影像组学  无创诊断  人工智能  
乳腺癌近红外激发荧光成像方法研究和临床应用探索 学位论文
, 中国科学院自动化研究所: 中国科学院大学, 2020
Authors:  张崇
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近红外激发荧光成像  手术导航  图像处理  乳腺癌  
Development and External Validation of Radiomics Approach for Nuclear Grading in Clear Cell Renal Cell Carcinoma 期刊论文
ANNALS OF SURGICAL ONCOLOGY, 2020, 卷号: 27, 期号: 10, 页码: 4057–4065
Authors:  Zhou, Hongyu;  Mao, Haixia;  Dong, Di;  Fang, Mengjie;  Gu, Dongsheng;  Liu, Xueling;  Xu, Min;  Yang, Shudong;  Zou, Jian;  Yin, Ruohan;  Zheng, Hairong;  Tian, Jie;  Pan, Changjie;  Fang, Xiangming;  Zhou, Hongyu;  Mao, Haixia;  Dong, Di;  Fang, Mengjie;  Gu, Dongsheng;  Liu, Xueling;  Xu, Min;  Yang, Shudong;  Zou, Jian;  Yin, Ruohan;  Zheng, Hairong;  Tian, Jie;  Pan, Changjie;  Fang, Xiangming
View  |  Adobe PDF(1325Kb)  |  Favorite  |  View/Download：29/3  |  Submit date：2020/06/22
Clear Cell Renal Cell Carcinoma  
Development and validation of a CT-based radiomic nomogram for preoperative prediction of early recurrence in advanced gastric cancer 期刊论文
RADIOTHERAPY AND ONCOLOGY, 2020, 卷号: 145, 期号: 1, 页码: 13-20
Authors:  Zhang, Wenjuan;  Fang, Mengjie;  Dong, Di;  Wang, Xiaoxiao;  Ke, Xiaoai;  Zhang, Liwen;  Hu, Chaoen;  Guo, Lingyun;  Guan, Xiaoying;  Zhou, Junlin;  Shan, Xiuhong;  Tian, Jie
View  |  Adobe PDF(1203Kb)  |  Favorite  |  View/Download：23/5  |  Submit date：2020/06/22
Gastric cancer  Computed tomography  Radiomics  Deep learning  Prognosis