Hasil Pencarian - Xueyi Zheng

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  1. 1
    Elaboration and Validation of a Nomogram Based on Axillary Ultrasound and Tumor Clinicopathological Features to Predict Axillary Lymph Node Metastasis in Patients With Breast Cancer

    Elaboration and Validation of a Nomogram Based on Axillary Ultrasound and Tumor Clinicopathological Features to Predict Axillary Lymph Node Metastasis in Patients With Breast Cance... oleh Yubo Liu, Feng Ye, Yun Wang, Xueyi Zheng, Yini Huang, Jianhua Zhou

    Diterbitkan 2022-05-01
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  2. 2
    Immunosuppressive Tumor Microenvironment and Immunotherapy of Epstein–Barr Virus-Associated Malignancies

    Immunosuppressive Tumor Microenvironment and Immunotherapy of Epstein–Barr Virus-Associated Malignancies oleh Xueyi Zheng, Yuhua Huang, Kai Li, Rongzhen Luo, Muyan Cai, Jingping Yun

    Diterbitkan 2022-05-01
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  3. 3
    Early differentiating between the chemotherapy responders and nonresponders: preliminary results with ultrasonic spectrum analysis of the RF time series in preclinical breast cancer models

    Early differentiating between the chemotherapy responders and nonresponders: preliminary results with ultrasonic spectrum analysis of the RF time series in preclinical breast cance... oleh Fei Li, Yini Huang, Jianwei Wang, Chunyi Lin, Qing Li, Xueyi Zheng, Yun Wang, Longhui Cao, Jianhua Zhou

    Diterbitkan 2019-08-01
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  4. 4
    Deep learning radiomics can predict axillary lymph node status in early-stage breast cancer

    Deep learning radiomics can predict axillary lymph node status in early-stage breast cancer oleh Xueyi Zheng, Zhao Yao, Yini Huang, Yanyan Yu, Yun Wang, Yubo Liu, Rushuang Mao, Fei Li, Yang Xiao, Yuanyuan Wang, Yixin Hu, Jinhua Yu, Jianhua Zhou

    Diterbitkan 2020-03-01
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  5. 5
    Author Correction: Deep learning radiomics can predict axillary lymph node status in early-stage breast cancer

    Author Correction: Deep learning radiomics can predict axillary lymph node status in early-stage breast cancer oleh Xueyi Zheng, Zhao Yao, Yini Huang, Yanyan Yu, Yun Wang, Yubo Liu, Rushuang Mao, Fei Li, Yang Xiao, Yuanyuan Wang, Yixin Hu, Jinhua Yu, Jianhua Zhou

    Diterbitkan 2021-07-01
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  6. 6
    A multicenter proof-of-concept study on deep learning-based intraoperative discrimination of primary central nervous system lymphoma

    A multicenter proof-of-concept study on deep learning-based intraoperative discrimination of primary central nervous system lymphoma oleh Xinke Zhang, Zihan Zhao, Ruixuan Wang, Haohua Chen, Xueyi Zheng, Lili Liu, Lilong Lan, Peng Li, Shuyang Wu, Qinghua Cao, Rongzhen Luo, Wanming Hu, Shanshan lyu, Zhengyu Zhang, Dan Xie, Yaping Ye, Yu Wang, Muyan Cai

    Diterbitkan 2024-05-01
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  7. 7
    C-Reactive Protein Levels Predict Responses to PD-1 Inhibitors in Hepatocellular Carcinoma Patients

    C-Reactive Protein Levels Predict Responses to PD-1 Inhibitors in Hepatocellular Carcinoma Patients oleh Yiyang Zhang, Yiyang Zhang, Yiyang Zhang, Lianghe Lu, Lianghe Lu, Zhangping He, Zhangping He, Zhishen Xu, Zhishen Xu, Zhicheng Xiang, Zhicheng Xiang, Run-Cong Nie, Run-Cong Nie, Wenping Lin, Wenping Lin, Wenxu Chen, Wenxu Chen, Jie Zhou, Jie Zhou, Yixin Yin, Yixin Yin, Juanjuan Xie, Juanjuan Xie, Youcheng Zhang, Youcheng Zhang, Xueyi Zheng, Xueyi Zheng, Tianchen Zhu, Tianchen Zhu, Xiaoxia Cai, Xiaoxia Cai, Peng Li, Peng Li, Xue Chao, Xue Chao, Mu-Yan Cai, Mu-Yan Cai

    Diterbitkan 2022-02-01
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  8. 8
    A deep learning model and human-machine fusion for prediction of EBV-associated gastric cancer from histopathology

    A deep learning model and human-machine fusion for prediction of EBV-associated gastric cancer from histopathology oleh Xueyi Zheng, Ruixuan Wang, Xinke Zhang, Yan Sun, Haohuan Zhang, Zihan Zhao, Yuanhang Zheng, Jing Luo, Jiangyu Zhang, Hongmei Wu, Dan Huang, Wenbiao Zhu, Jianning Chen, Qinghua Cao, Hong Zeng, Rongzhen Luo, Peng Li, Lilong Lan, Jingping Yun, Dan Xie, Wei-Shi Zheng, Junhang Luo, Muyan Cai

    Diterbitkan 2022-05-01
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  9. 9
    An interpretable deep learning model for identifying the morphological characteristics of dMMR/MSI-H gastric cancer

    An interpretable deep learning model for identifying the morphological characteristics of dMMR/MSI-H gastric cancer oleh Xueyi Zheng, Bingzhong Jing, Zihan Zhao, Ruixuan Wang, Xinke Zhang, Haohua Chen, Shuyang Wu, Yan Sun, Jiangyu Zhang, Hongmei Wu, Dan Huang, Wenbiao Zhu, Jianning Chen, Qinghua Cao, Hong Zeng, Jinling Duan, Yuanliang Luo, Zhicheng Li, Wuhao Lin, Runcong Nie, Yishu Deng, Jingping Yun, Chaofeng Li, Dan Xie, Muyan Cai

    Diterbitkan 2024-03-01
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