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Counterfactual Supporting Facts Extraction for Explainable Medical Record Based Diagnosis with Graph Network 会议论文
, Online, June 6–11, 2021
作者:  Wu HR(吴浩然);  Chen W(陈炜);  Xu S(徐爽);  Xu B(徐波)
Adobe PDF(1394Kb)  |  收藏  |  浏览/下载:168/58  |  提交时间:2023/06/26
CT-based radiomics to predict development of macrovascular invasion in hepatocellular carcinoma: A multicenter study 期刊论文
Hepatobiliary & Pancreatic Diseases International, 2021, 卷号: 2021, 期号: --, 页码: --
作者:  Jingwei Wei;  Sirui Fu;  Jie Zhang;  Dongsheng Gu;  Xiaoqun Li;  Xudong Chen;  Shuaitong Zhang;  Xiaofei He;  Jianfeng Yan;  Ligong Lu;  Jie Tian
Adobe PDF(1564Kb)  |  收藏  |  浏览/下载:182/41  |  提交时间:2022/04/06
Computed tomography  Hepatocellular carcinoma  Macrovascular invasion  Prognosis  Radiomics  
基于调强放疗大数据的患者剂量验证方法建模研究 学位论文
工学博士, 中国科学院自动化所: 中国科学院大学, 2021
作者:  王乐
Adobe PDF(5726Kb)  |  收藏  |  浏览/下载:191/2  |  提交时间:2022/03/07
肿瘤放射治疗,机器学习,深度学习,预测分类,基于患者的剂量验证, 容积旋转调强治疗  
Deep learning radiomics of ultrasonography can predict response to neoadjuvant chemotherapy in breast cancer at an early stage of treatment: a prospective study 期刊论文
EUROPEAN RADIOLOGY, 2021, 页码: 11
作者:  Gu, Jionghui;  Tong, Tong;  He, Chang;  Xu, Min;  Yang, Xin;  Tian, Jie;  Jiang, Tianan;  Wang, Kun
Adobe PDF(3007Kb)  |  收藏  |  浏览/下载:281/49  |  提交时间:2021/12/28
Breast cancer  Deep learning  Neoadjuvant chemotherapy  Ultrasonography  Treatment outcome  
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:377/70  |  提交时间:2021/11/03
Multi-task deep learning  Radiomic nomogram  Survival analysis  Treatment decision  Advanced nasopharyngeal carcinoma  
Commissioning and clinical implementation of an Autoencoder based Classification-Regression model for VMAT patient-specific QA in a multi-institution scenario 期刊论文
RADIOTHERAPY AND ONCOLOGY, 2021, 卷号: 161, 期号: 10.1016/j.radonc.2021.06.024, 页码: 230-240
作者:  Yang, Ruijie;  Yang, Xueying;  Wang, Le;  Li, Dingjie;  Guo, Yuexin;  Li, Ying;  Guan, Yumin;  Wu, Xiangyang;  Xu, Shouping;  Zhang, Shuming;  Chan, Maria F.;  Geng, Lisheng;  Sui, Jing
Adobe PDF(2840Kb)  |  收藏  |  浏览/下载:373/60  |  提交时间:2021/11/02
Machine learning  VMAT patient-specific QA  Multi-institution validation  Commissioning  Clinical implementation  
A review of the application of machine learning in molecular imaging 期刊论文
Annals of Translational Medicine, 2021, 卷号: 0, 期号: 0, 页码: 0
作者:  Yin, Lin;  Cao, Zhen;  Wang, Kun;  Tian, Jie;  Yang, Xing;  Zhang, Jianhua
Adobe PDF(4435Kb)  |  收藏  |  浏览/下载:191/38  |  提交时间:2021/06/16
molecular imaging, machine learning, artificial intelligence  
基于Unet编码块迁移学习的胃印戒细胞癌诊断研究 学位论文
, 北京市海淀区中国科学院自动化研究所智能化大厦910: 中国科学院大学-中国科学院自动化研究所, 2021
作者:  李聪
Adobe PDF(3289Kb)  |  收藏  |  浏览/下载:240/5  |  提交时间:2021/06/16
胃印戒细胞癌  迁移学习  深度学习  诊断  生存期  
Application of deep learning to predict underestimation in ductal carcinoma in situ of the breast with ultrasound 期刊论文
ANNALS OF TRANSLATIONAL MEDICINE, 2021, 卷号: 9, 期号: 4, 页码: 9
作者:  Qian, Lang;  Lv, Zhikun;  Zhang, Kai;  Wang, Kun;  Zhu, Qian;  Zhou, Shichong;  Chang, Cai;  Tian, Jie
Adobe PDF(743Kb)  |  收藏  |  浏览/下载:326/64  |  提交时间:2021/04/21
Artificial intelligence (AI)  ductal carcinoma in situ (DCIS)  core needle biopsy (CNB)  prediction of upstaging  
Integrating No.3 lymph nodes and primary tumor radiomics to predict lymph node metastasis in T1-2 gastric cancer 期刊论文
BMC Medical Imaging, 2021, 卷号: 21, 期号: 1, 页码: 10
作者:  Wang,Xiaoxiao;  Li,Cong;  Fang,Mengjie;  Zhang,Liwen;  Zhong,Lianzhen;  Dong,Di;  Tian,Jie;  Shan,Xiuhong
Adobe PDF(2269Kb)  |  收藏  |  浏览/下载:403/64  |  提交时间:2021/04/06
Stomach cancer  Lymph nodes  Nomogram