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Chen Jiang Wu

Showing results (1-10 of 33) with videos related to

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European Journal of Radiology|May 25, 2015
Hypertrophic cardiomyopathy: Cardiac structural and microvascular abnormalities as evaluated with multi-parametric MRIYu-Dong Zhang, Meijiao Li, Liang Qi, et al.
AJR. American Journal of Roentgenology|July 12, 2018
Construction of a Preoperative Radiologic-Risk Signature for Predicting the Pathologic Status of Prostate Cancer at Radical ProstatectomyLiang Qi, Chen-Jiang Wu, Jing Zhang, et al.
Journal of Magnetic Resonance Imaging : JMRI|February 14, 2018
Using support vector machine analysis to assess PartinMR: A new prediction model for organ-confined prostate cancerJing Wang, Chen-Jiang Wu, Mei-Ling Bao, et al.
Diagnostic and Interventional Radiology (Ankara, Turkey)|December 1, 2025
Texture analysis enhances diagnostic accuracy of lesions scored as 5 in the Prostate Imaging Reporting and Data System in magnetic resonance imagingYan Bai, Xin Ru Xie, Ying Hou, et al.
Abdominal Radiology (New York)|August 3, 2020
A radiomics machine learning-based redefining score robustly identifies clinically significant prostate cancer in equivocal PI-RADS score 3 lesionsYing Hou, Mei-Ling Bao, Chen-Jiang Wu, et al.
BJU International|August 9, 2019
A machine learning-assisted decision-support model to better identify patients with prostate cancer requiring an extended pelvic lymph node dissectionYing Hou, Mei-Ling Bao, Chen-Jiang Wu, et al.
European Radiology|April 5, 2017
Machine learning-based analysis of MR radiomics can help to improve the diagnostic performance of PI-RADS v2 in clinically relevant prostate cancerJing Wang, Chen-Jiang Wu, Mei-Ling Bao, et al.
Abdominal Radiology (New York)|August 10, 2016
Feasibility of triphasic CT with a modified two-point Patlak plot to determine spit kidney glomerular filtration rate in clinical practiceYu-Dong Zhang, Chen-Qi Xue, Chen-Jiang Wu, et al.
Magnetic Resonance Imaging|May 26, 2015
Feasibility study of high-resolution DCE-MRI for glomerular filtration rate (GFR) measurement in a routine clinical modalYu-Dong Zhang, Chen-Jiang Wu, Jing Zhang, et al.
Journal of Magnetic Resonance Imaging : JMRI|October 19, 2020
Optimized MRI Assessment for Clinically Significant Prostate Cancer: A STARD-Compliant Two-Center StudyJie Bao, Rui Zhi, Ying Hou, et al.
Pageof 4

Showing results (1-10 of 33) with videos related to

Sort By:
Pageof 4
European Journal of Radiology|May 25, 2015
Hypertrophic cardiomyopathy: Cardiac structural and microvascular abnormalities as evaluated with multi-parametric MRIYu-Dong Zhang, Meijiao Li, Liang Qi, et al.
AJR. American Journal of Roentgenology|July 12, 2018
Construction of a Preoperative Radiologic-Risk Signature for Predicting the Pathologic Status of Prostate Cancer at Radical ProstatectomyLiang Qi, Chen-Jiang Wu, Jing Zhang, et al.
Journal of Magnetic Resonance Imaging : JMRI|February 14, 2018
Using support vector machine analysis to assess PartinMR: A new prediction model for organ-confined prostate cancerJing Wang, Chen-Jiang Wu, Mei-Ling Bao, et al.
Diagnostic and Interventional Radiology (Ankara, Turkey)|December 1, 2025
Texture analysis enhances diagnostic accuracy of lesions scored as 5 in the Prostate Imaging Reporting and Data System in magnetic resonance imagingYan Bai, Xin Ru Xie, Ying Hou, et al.
Abdominal Radiology (New York)|August 3, 2020
A radiomics machine learning-based redefining score robustly identifies clinically significant prostate cancer in equivocal PI-RADS score 3 lesionsYing Hou, Mei-Ling Bao, Chen-Jiang Wu, et al.
BJU International|August 9, 2019
A machine learning-assisted decision-support model to better identify patients with prostate cancer requiring an extended pelvic lymph node dissectionYing Hou, Mei-Ling Bao, Chen-Jiang Wu, et al.
European Radiology|April 5, 2017
Machine learning-based analysis of MR radiomics can help to improve the diagnostic performance of PI-RADS v2 in clinically relevant prostate cancerJing Wang, Chen-Jiang Wu, Mei-Ling Bao, et al.
Abdominal Radiology (New York)|August 10, 2016
Feasibility of triphasic CT with a modified two-point Patlak plot to determine spit kidney glomerular filtration rate in clinical practiceYu-Dong Zhang, Chen-Qi Xue, Chen-Jiang Wu, et al.
Magnetic Resonance Imaging|May 26, 2015
Feasibility study of high-resolution DCE-MRI for glomerular filtration rate (GFR) measurement in a routine clinical modalYu-Dong Zhang, Chen-Jiang Wu, Jing Zhang, et al.
Journal of Magnetic Resonance Imaging : JMRI|October 19, 2020
Optimized MRI Assessment for Clinically Significant Prostate Cancer: A STARD-Compliant Two-Center StudyJie Bao, Rui Zhi, Ying Hou, et al.
Pageof 4