Jiuquan Zhang

4.0k total citations
166 papers, 2.8k citations indexed

About

Jiuquan Zhang is a scholar working on Radiology, Nuclear Medicine and Imaging, Neurology and Cognitive Neuroscience. According to data from OpenAlex, Jiuquan Zhang has authored 166 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 110 papers in Radiology, Nuclear Medicine and Imaging, 32 papers in Neurology and 30 papers in Cognitive Neuroscience. Recurrent topics in Jiuquan Zhang's work include Radiomics and Machine Learning in Medical Imaging (46 papers), MRI in cancer diagnosis (40 papers) and Advanced Neuroimaging Techniques and Applications (27 papers). Jiuquan Zhang is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (46 papers), MRI in cancer diagnosis (40 papers) and Advanced Neuroimaging Techniques and Applications (27 papers). Jiuquan Zhang collaborates with scholars based in China, United States and Canada. Jiuquan Zhang's co-authors include Jian Wang, Lihua Chen, Daihong Liu, Xuntao Yin, Luqing Wei, Yanling Zhang, Xuequan Huang, Xiaofei Hu, Yuanchao Zhang and Yunbao Xia and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Neurology.

In The Last Decade

Jiuquan Zhang

154 papers receiving 2.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jiuquan Zhang China 31 1.5k 726 637 332 222 166 2.8k
Shingo Kakeda Japan 24 1.0k 0.7× 387 0.5× 459 0.7× 401 1.2× 270 1.2× 117 2.1k
Christian Langkammer Austria 37 2.5k 1.7× 1.0k 1.4× 729 1.1× 322 1.0× 350 1.6× 85 4.9k
Thomas Tourdias France 31 909 0.6× 673 0.9× 393 0.6× 454 1.4× 288 1.3× 115 2.5k
Francesca B. Pizzini Italy 31 901 0.6× 533 0.7× 519 0.8× 184 0.6× 201 0.9× 105 2.8k
Jacques Darcourt France 27 1.1k 0.8× 821 1.1× 533 0.8× 287 0.9× 277 1.2× 112 3.0k
Akifumi Hagiwara Japan 28 1.9k 1.3× 371 0.5× 271 0.4× 156 0.5× 360 1.6× 151 2.7k
Deqiang Qiu United States 27 1.3k 0.9× 222 0.3× 737 1.2× 351 1.1× 192 0.9× 85 2.6k
Sadahiko Nishizawa Japan 27 1.1k 0.7× 368 0.5× 489 0.8× 576 1.7× 171 0.8× 105 2.6k
Anna Tietze Germany 24 723 0.5× 829 1.1× 216 0.3× 269 0.8× 380 1.7× 96 2.5k
Bettina Beuthien‐Baumann Germany 31 1.5k 1.0× 481 0.7× 582 0.9× 592 1.8× 141 0.6× 108 3.3k

Countries citing papers authored by Jiuquan Zhang

Since Specialization
Citations

This map shows the geographic impact of Jiuquan Zhang'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 Jiuquan Zhang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jiuquan Zhang more than expected).

Fields of papers citing papers by Jiuquan Zhang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jiuquan Zhang. 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 Jiuquan Zhang. The network helps show where Jiuquan Zhang may publish in the future.

Co-authorship network of co-authors of Jiuquan Zhang

This figure shows the co-authorship network connecting the top 25 collaborators of Jiuquan Zhang. A scholar is included among the top collaborators of Jiuquan Zhang 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 Jiuquan Zhang. Jiuquan Zhang 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.
Zheng, Jiahui, Chengfang Wang, Yu Tang, et al.. (2025). Structural and functional connectivity coupling as an imaging marker for bone metastasis pain in lung cancer patients. Brain Research Bulletin. 221. 111210–111210.
2.
Huang, Yao, Xiaoxia Wang, Xiaofei Hu, et al.. (2025). Nomogram for Predicting Neoadjuvant Chemotherapy Response in Breast Cancer Using MRI-based Intratumoral Heterogeneity Quantification. Radiology. 315(1). e241805–e241805. 2 indexed citations
3.
Ren, Huanhuan, Diwei Shi, Junhao Huang, et al.. (2025). Differentiating Benign Thyroid Nodules and Papillary Thyroid Carcinoma Using Time‐Dependent Diffusion MRI : A Feasibility Study. Journal of Magnetic Resonance Imaging. 62(6). 1649–1660. 1 indexed citations
4.
Wang, Xiaoxia, et al.. (2025). Time‐Dependent Diffusion MRI ‐Based Microstructural Mapping for Characterizing HER2 ‐Zero, ‐Low, ‐Ultra‐Low, and ‐Positive Breast Cancer. Journal of Magnetic Resonance Imaging. 62(6). 1754–1767. 1 indexed citations
5.
6.
Ren, Huanhuan, Junhao Huang, Yao Huang, et al.. (2025). Nomogram based on dual-energy computed tomography to predict the response to induction chemotherapy in patients with nasopharyngeal carcinoma: a two-center study. Cancer Imaging. 25(1). 8–8. 1 indexed citations
7.
Li, Xiaoqin, et al.. (2024). Longitudinal Evaluation of Coronary Arteries and Myocardium in Breast Cancer Using Coronary Computed Tomographic Angiography. JACC. Cardiovascular imaging. 17(11). 1335–1347. 2 indexed citations
8.
Shi, Jinfang, et al.. (2024). Evaluation of Splenic Involvement in Lymphomas Using Extracellular Volume Fraction Computed Tomography. Journal of Computer Assisted Tomography. 49(2). 225–233.
9.
10.
Wang, Xiaoxia, Jing Zhang, Daihong Liu, et al.. (2023). Dual-energy CT: A new frontier in oncology imaging. SHILAP Revista de lepidopterología. 1(3). 100044–100044. 3 indexed citations
11.
Zhang, Jiuquan, Xiaodong Teng, Qi Lai, et al.. (2023). 1MO Image biomarker discovery from DCE-MRI for identifying responders of MK-2206 on early-stage breast cancer patients: A secondary radio-genomics analysis of I-SPY2 trial. Annals of Oncology. 34. S1468–S1468. 1 indexed citations
12.
13.
Huang, Yao, Xiaofei Hu, Lan Li, et al.. (2023). Early Identification of Pathologic Complete Response to Neoadjuvant Chemotherapy Using Multiphase DCE‐MRI by Siamese Network in Breast Cancer: A Longitudinal Multicenter Study. Journal of Magnetic Resonance Imaging. 60(4). 1325–1337. 2 indexed citations
14.
Liu, Daihong, Yong Tan, Hong Yu, et al.. (2022). Altered brain functional activity and connectivity in bone metastasis pain of lung cancer patients: A preliminary resting-state fMRI study. Frontiers in Neurology. 13. 936012–936012. 8 indexed citations
15.
Li, Haotian, Yi‐Cheng Hsu, Zhiyong Zhao, et al.. (2022). Inversion‐Recovery‐Prepared Oscillating Gradient Sequence Improves Diffusion‐Time Dependency Measurements in the Human Brain. Journal of Magnetic Resonance Imaging. 57(2). 446–453. 3 indexed citations
16.
Ma, Xujing, Fengmei Lu, Heng Chen, et al.. (2020). Static and dynamic alterations in the amplitude of low-frequency fluctuation in patients with amyotrophic lateral sclerosis. PeerJ. 8. e10052–e10052. 14 indexed citations
17.
Zhang, Yuanchao, Ting Qiu, Jinlei Zhang, et al.. (2018). Abnormal topological organization of structural covariance networks in amyotrophic lateral sclerosis. NeuroImage Clinical. 21. 101619–101619. 33 indexed citations
18.
Xu, Jinping, Jiuquan Zhang, Jinlei Zhang, et al.. (2017). Abnormalities in Structural Covariance of Cortical Gyrification in Parkinson's Disease. Frontiers in Neuroanatomy. 11. 12–12. 13 indexed citations
19.
Zhang, Jiuquan, Luqing Wei, Xiaofei Hu, et al.. (2014). Akinetic-rigid and tremor-dominant Parkinson's disease patients show different patterns of intrinsic brain activity. Parkinsonism & Related Disorders. 21(1). 23–30. 87 indexed citations
20.
Zhang, Lingxiao, Jiuquan Zhang, Stephen Kyei‐Boahen, & Minghua Zhang. (2010). Simulation and Prediction of Soybean Growth and Development under Field Conditions. CGSPace A Repository of Agricultural Research Outputs (Consultative Group for International Agricultural Research). 7(4). 374–385. 22 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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