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Qijun Shen

Showing results (11-20 of 18) with videos related to

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European Radiology|November 8, 2023
Prediction of early hematoma expansion of spontaneous intracerebral hemorrhage based on deep learning radiomics features of noncontrast computed tomographyChangfeng Feng, Zhongxiang Ding, Qun Lao, et al.
Oncotarget|March 1, 2018
Prognostic role of the primary tumour site in patients with operable small intestine and gastrointestinal stromal tumours: a large population-based analysisHua Ye, Hua Xin, Qi Zheng, et al.
Frontiers in Oncology|June 3, 2026
Interpretable deep learning-based hierarchical multi-modal fusion model for predicting HER2 expression in gastric cancerChenxi Hu, Changfeng Feng, Ziyi Ye, et al.
European Radiology|August 7, 2020
Risk stratification of thymic epithelial tumors by using a nomogram combined with radiomic features and TNM stagingQijun Shen, Yanna Shan, Wen Xu, et al.
Cancer Management and Research|February 27, 2020
New Preoperative Nomogram Using the Centrality Index to Predict High Nuclear Grade Clear Cell Renal CarcinomaZhan Feng, Shuangshuang Lou, Lixia Zhang, et al.
European Radiology|May 2, 2018
Quantitative parameters of CT texture analysis as potential markersfor early prediction of spontaneous intracranial hemorrhage enlargementQijun Shen, Yanna Shan, Zhengyu Hu, et al.
Frontiers in Oncology|June 1, 2022
Radiomics Based on DCE-MRI Improved Diagnostic Performance Compared to BI-RADS Analysis in Identifying Sclerosing Adenosis of the BreastMei Ruan, Zhongxiang Ding, Yanna Shan, et al.
Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society|August 14, 2025
Prediction of hematoma changes in spontaneous intracerebral hemorrhage using a Transformer-based generative adversarial network to generate follow-up CT imagesChangfeng Feng, Caiwen Jiang, Chenxi Hu, et al.
Pageof 2

Showing results (11-20 of 18) with videos related to

Sort By:
Pageof 2
You have reached the last page of results.This site can display upto 18 results.
European Radiology|November 8, 2023
Prediction of early hematoma expansion of spontaneous intracerebral hemorrhage based on deep learning radiomics features of noncontrast computed tomographyChangfeng Feng, Zhongxiang Ding, Qun Lao, et al.
Oncotarget|March 1, 2018
Prognostic role of the primary tumour site in patients with operable small intestine and gastrointestinal stromal tumours: a large population-based analysisHua Ye, Hua Xin, Qi Zheng, et al.
Frontiers in Oncology|June 3, 2026
Interpretable deep learning-based hierarchical multi-modal fusion model for predicting HER2 expression in gastric cancerChenxi Hu, Changfeng Feng, Ziyi Ye, et al.
European Radiology|August 7, 2020
Risk stratification of thymic epithelial tumors by using a nomogram combined with radiomic features and TNM stagingQijun Shen, Yanna Shan, Wen Xu, et al.
Cancer Management and Research|February 27, 2020
New Preoperative Nomogram Using the Centrality Index to Predict High Nuclear Grade Clear Cell Renal CarcinomaZhan Feng, Shuangshuang Lou, Lixia Zhang, et al.
European Radiology|May 2, 2018
Quantitative parameters of CT texture analysis as potential markersfor early prediction of spontaneous intracranial hemorrhage enlargementQijun Shen, Yanna Shan, Zhengyu Hu, et al.
Frontiers in Oncology|June 1, 2022
Radiomics Based on DCE-MRI Improved Diagnostic Performance Compared to BI-RADS Analysis in Identifying Sclerosing Adenosis of the BreastMei Ruan, Zhongxiang Ding, Yanna Shan, et al.
Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society|August 14, 2025
Prediction of hematoma changes in spontaneous intracerebral hemorrhage using a Transformer-based generative adversarial network to generate follow-up CT imagesChangfeng Feng, Caiwen Jiang, Chenxi Hu, et al.
Pageof 2