Yuqin Ding

940 total citations
37 papers, 640 citations indexed

About

Yuqin Ding is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Biomedical Engineering. According to data from OpenAlex, Yuqin Ding has authored 37 papers receiving a total of 640 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Radiology, Nuclear Medicine and Imaging, 12 papers in Pulmonary and Respiratory Medicine and 11 papers in Biomedical Engineering. Recurrent topics in Yuqin Ding's work include MRI in cancer diagnosis (12 papers), Advanced X-ray and CT Imaging (11 papers) and Advanced Neuroimaging Techniques and Applications (8 papers). Yuqin Ding is often cited by papers focused on MRI in cancer diagnosis (12 papers), Advanced X-ray and CT Imaging (11 papers) and Advanced Neuroimaging Techniques and Applications (8 papers). Yuqin Ding collaborates with scholars based in China, United States and Germany. Yuqin Ding's co-authors include Jianjun Zhou, Mengsu Zeng, Wei Mao, Caixia Fu, Shengxiang Rao, Caizhong Chen, Yaqiong Wang, Xiaoqiang Ding, Jun Hou and Mengsu Zeng and has published in prestigious journals such as Journal of Clinical Oncology, Radiology and Expert Systems with Applications.

In The Last Decade

Yuqin Ding

36 papers receiving 635 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yuqin Ding China 17 445 179 119 97 80 37 640
Ke Lv China 10 145 0.3× 104 0.6× 95 0.8× 79 0.8× 64 0.8× 33 384
Hong Il Ha South Korea 13 170 0.4× 156 0.9× 85 0.7× 193 2.0× 126 1.6× 39 476
Daniella F. Pinho United States 14 590 1.3× 260 1.5× 436 3.7× 88 0.9× 76 0.9× 28 828
Thomas Fischer Germany 15 207 0.5× 424 2.4× 114 1.0× 214 2.2× 30 0.4× 40 807
M. Raquel Oliva United States 9 200 0.4× 286 1.6× 58 0.5× 142 1.5× 62 0.8× 13 536
Zhengbiao Ji China 12 132 0.3× 112 0.6× 93 0.8× 103 1.1× 41 0.5× 28 344
Hester Burger South Africa 13 215 0.5× 97 0.5× 50 0.4× 72 0.7× 27 0.3× 36 445
Robert Kaatee Netherlands 11 295 0.7× 668 3.7× 237 2.0× 268 2.8× 18 0.2× 20 978
Soo Buem Cho South Korea 12 179 0.4× 136 0.8× 73 0.6× 165 1.7× 21 0.3× 51 537
Fritz Schaefer Germany 14 173 0.4× 151 0.8× 116 1.0× 215 2.2× 22 0.3× 27 477

Countries citing papers authored by Yuqin Ding

Since Specialization
Citations

This map shows the geographic impact of Yuqin Ding's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yuqin Ding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuqin Ding more than expected).

Fields of papers citing papers by Yuqin Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yuqin Ding. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yuqin Ding. The network helps show where Yuqin Ding may publish in the future.

Co-authorship network of co-authors of Yuqin Ding

This figure shows the co-authorship network connecting the top 25 collaborators of Yuqin Ding. A scholar is included among the top collaborators of Yuqin Ding based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yuqin Ding. Yuqin Ding is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Liu, Jiahao, et al.. (2025). GMMNet: A precise classification model for rice grains during rice processing. Expert Systems with Applications. 287. 128223–128223.
2.
Min, Lingqiang, Bo Zhou, Peng Zhou, et al.. (2024). Transarterial Infusion Chemotherapy and Embolization for Patients With Unresectable Advanced Cancer of Stomach or Gastroesophageal Junction: A Retrospective Study. Cancer Medicine. 13(21). e70396–e70396. 1 indexed citations
3.
Wang, Ruiting, et al.. (2024). Potential of quantitative T1 mapping to serve as a novel prognostic predictor of clear cell renal cell carcinoma after nephrectomy. Quantitative Imaging in Medicine and Surgery. 14(10). 7600–7611. 1 indexed citations
4.
Mao, Wei, Yuqin Ding, Xiaoqiang Ding, et al.. (2023). Value of T1 Mapping in the Non-invasive Assessment of Renal Pathologic Injury for Chronic Kidney Disease Patients. Magnetic Resonance in Medical Sciences. 24(1). 78–87. 4 indexed citations
5.
6.
Lyu, Peijie, Nana Liu, Brian Harrawood, et al.. (2022). Is it possible to use low-dose deep learning reconstruction for the detection of liver metastases on CT routinely?. European Radiology. 33(3). 1629–1640. 25 indexed citations
7.
Mao, Wei, Yuqin Ding, Xiaoqiang Ding, et al.. (2022). Capability of arterial spin labeling and intravoxel incoherent motion diffusion-weighted imaging to detect early kidney injury in chronic kidney disease. European Radiology. 33(5). 3286–3294. 18 indexed citations
8.
Mao, Wei, Xiaoqiang Ding, Yuqin Ding, et al.. (2022). Evaluation of interstitial fibrosis in chronic kidney disease by multiparametric functional MRI and histopathologic analysis. European Radiology. 33(6). 4138–4147. 17 indexed citations
9.
Lafata, Kyle J., Cai Li, Mathias Meyer, et al.. (2021). CT Radiomic Features of Superior Mesenteric Artery Involvement in Pancreatic Ductal Adenocarcinoma: A Pilot Study. Radiology. 301(3). 610–622. 42 indexed citations
10.
Schwartz, Fides R., Darin P. Clark, Yuqin Ding, et al.. (2021). Evaluating renal lesions using deep-learning based extension of dual-energy FoV in dual-source CT—A retrospective pilot study. European Journal of Radiology. 139. 109734–109734. 3 indexed citations
11.
Mao, Wei, Yuqin Ding, Xiaoqiang Ding, et al.. (2021). Diffusion kurtosis imaging for the assessment of renal fibrosis of chronic kidney disease: A preliminary study. Magnetic Resonance Imaging. 80. 113–120. 19 indexed citations
12.
Lyu, Peijie, Justin Solomon, Yuqin Ding, et al.. (2021). Effect of deep learning image reconstruction in the prediction of resectability of pancreatic cancer: Diagnostic performance and reader confidence. European Journal of Radiology. 141. 109825–109825. 29 indexed citations
13.
Ding, Yuqin, Daniele Marin, Federica Vernuccio, et al.. (2020). Variability of quantitative measurements of metastatic liver lesions: a multi-radiation-dose-level and multi-reader comparison. Abdominal Radiology. 46(1). 226–236. 4 indexed citations
14.
Ding, Yuqin, Andreas Richter, Wolfram Stiller, Hans‐Ulrich Kauczor, & Tim Frederik Weber. (2019). Association between true non-contrast and virtual non-contrast vertebral bone CT attenuation values determined using dual-layer spectral detector CT. European Journal of Radiology. 121. 108740–108740. 8 indexed citations
15.
Ding, Yuqin, Wei Mao, Xiaoyi Hu, et al.. (2019). Differentiating between malignant and benign renal tumors: do IVIM and diffusion kurtosis imaging perform better than DWI?. European Radiology. 29(12). 6930–6939. 65 indexed citations
16.
17.
Mao, Wei, Jianjun Zhou, Mengsu Zeng, et al.. (2017). Intravoxel incoherent motion diffusion-weighted imaging for the assessment of renal fibrosis of chronic kidney disease: A preliminary study. Magnetic Resonance Imaging. 47. 118–124. 55 indexed citations
18.
Ding, Yuqin, et al.. (2015). Liver fibrosis staging using T1 mapping on gadoxetic acid-enhanced MRI compared with DW imaging. Clinical Radiology. 70(10). 1096–1103. 49 indexed citations
19.
Zhou, Jianjun, et al.. (2013). Homogeneous high attenuation renal cysts and solid masses - differentiation with single phase dual energy computed tomography. Clinical Radiology. 68(4). e198–e205. 15 indexed citations
20.
Ye, Mingfu, Yunchao Li, Haizheng Zhong, et al.. (2010). Synthesis of Sb<SUB>2</SUB>E<SUB>3</SUB> (E = S, Se) Nanorods with a Flat Cross Section by a Rapid Hot Injection Method. Journal of Nanoscience and Nanotechnology. 10(11). 7778–7782. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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