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Enming Cui

Showing results (31-40 of 39) with videos related to

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Frontiers in Oncology|October 3, 2022
Predicting lymphovascular invasion in clinically node-negative breast cancer detected by abbreviated magnetic resonance imaging: Transfer learning vs. radiomicsBao Feng, Zhuangsheng Liu, Yu Liu, et al.
Journal of Magnetic Resonance Imaging : JMRI|February 19, 2019
Preoperative prediction of lymphovascular invasion in invasive breast cancer with dynamic contrast-enhanced-MRI-based radiomicsZhuangsheng Liu, Bao Feng, Changlin Li, et al.
Cancer Imaging : the Official Publication of the International Cancer Imaging Society|July 10, 2020
A CT-based radiomics nomogram for prediction of lung adenocarcinomas and granulomatous lesions in patient with solitary sub-centimeter solid nodulesXiangmeng Chen, Bao Feng, Yehang Chen, et al.
Academic Radiology|May 22, 2026
Preoperative Risk Assessment of Adrenal Metastases in a Multicenter Study: Development of a Robust Federated Learning ModelBao Feng, Zhaole Yu, Yehang Chen, et al.
Nature Communications|March 2, 2025
General lightweight framework for vision foundation model supporting multi-task and multi-center medical image analysisSenliang Lu, Yehang Chen, Yuan Chen, et al.
Nature Communications|January 25, 2024
Robustly federated learning model for identifying high-risk patients with postoperative gastric cancer recurrenceBao Feng, Jiangfeng Shi, Liebin Huang, et al.
Cancers|February 11, 2023
Identifying Solitary Granulomatous Nodules from Solid Lung Adenocarcinoma: Exploring Robust Image Features with Cross-Domain Transfer LearningBao Feng, Xiangmeng Chen, Yehang Chen, et al.
Iscience|December 5, 2024
AI-based fingerprint index of visceral adipose tissue for the prediction of bowel damage in patients with Crohn's diseaseXuehua Li, Cicong Hu, Haipeng Wang, et al.
Eclinicalmedicine|January 9, 2023
CT-based radiomics signature of visceral adipose tissue for prediction of disease progression in patients with Crohn's disease: A multicentre cohort studyXuehua Li, Naiwen Zhang, Cicong Hu, et al.
Pageof 4

Showing results (31-40 of 39) with videos related to

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Pageof 4
You have reached the last page of results.This site can display upto 39 results.
Frontiers in Oncology|October 3, 2022
Predicting lymphovascular invasion in clinically node-negative breast cancer detected by abbreviated magnetic resonance imaging: Transfer learning vs. radiomicsBao Feng, Zhuangsheng Liu, Yu Liu, et al.
Journal of Magnetic Resonance Imaging : JMRI|February 19, 2019
Preoperative prediction of lymphovascular invasion in invasive breast cancer with dynamic contrast-enhanced-MRI-based radiomicsZhuangsheng Liu, Bao Feng, Changlin Li, et al.
Cancer Imaging : the Official Publication of the International Cancer Imaging Society|July 10, 2020
A CT-based radiomics nomogram for prediction of lung adenocarcinomas and granulomatous lesions in patient with solitary sub-centimeter solid nodulesXiangmeng Chen, Bao Feng, Yehang Chen, et al.
Academic Radiology|May 22, 2026
Preoperative Risk Assessment of Adrenal Metastases in a Multicenter Study: Development of a Robust Federated Learning ModelBao Feng, Zhaole Yu, Yehang Chen, et al.
Nature Communications|March 2, 2025
General lightweight framework for vision foundation model supporting multi-task and multi-center medical image analysisSenliang Lu, Yehang Chen, Yuan Chen, et al.
Nature Communications|January 25, 2024
Robustly federated learning model for identifying high-risk patients with postoperative gastric cancer recurrenceBao Feng, Jiangfeng Shi, Liebin Huang, et al.
Cancers|February 11, 2023
Identifying Solitary Granulomatous Nodules from Solid Lung Adenocarcinoma: Exploring Robust Image Features with Cross-Domain Transfer LearningBao Feng, Xiangmeng Chen, Yehang Chen, et al.
Iscience|December 5, 2024
AI-based fingerprint index of visceral adipose tissue for the prediction of bowel damage in patients with Crohn's diseaseXuehua Li, Cicong Hu, Haipeng Wang, et al.
Eclinicalmedicine|January 9, 2023
CT-based radiomics signature of visceral adipose tissue for prediction of disease progression in patients with Crohn's disease: A multicentre cohort studyXuehua Li, Naiwen Zhang, Cicong Hu, et al.
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