Yi Wang
About
Yi Wang is a scholar working on Radiology, Nuclear Medicine and Imaging, Neurology and Pathology and Forensic Medicine.
According to data from OpenAlex, Yi Wang has authored 331 papers receiving a total of 10.1k indexed citations (citations by other indexed papers that have themselves been cited), including 214 papers in Radiology, Nuclear Medicine and Imaging, 47 papers in Neurology and 38 papers in Pathology and Forensic Medicine. Recurrent topics in Yi Wang's work include Advanced MRI Techniques and Applications (151 papers), Advanced Neuroimaging Techniques and Applications (78 papers) and Cardiac Imaging and Diagnostics (39 papers). Yi Wang is often cited by papers focused on Advanced MRI Techniques and Applications (151 papers), Advanced Neuroimaging Techniques and Applications (78 papers) and Cardiac Imaging and Diagnostics (39 papers). Yi Wang collaborates with scholars based in United States, China and South Korea. Yi Wang's co-authors include Tian Liu, Pascal Spincemaille, Martin R. Prince, Thanh D. Nguyen, Weiwei Chen, Ludovic de Rochefort, Susan A. Gauthier, Ajay Gupta, Tian Liu and Cynthia Wisnieff and has published in prestigious journals such as Proceedings of the National Academy of Sciences, PLoS ONE and Journal of Applied Physics.
In The Last Decade
Yi Wang
302 papers receiving 10.0k citations
Hit Papers
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late) cites · hero ref
| Name | h | Career | Trend | Papers | Cites | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| Yi Wang United States | 51 | 6.8k | 1.7k | 1.1k | 1.0k | 985 | 331 | 10.1k | ||
| Xavier Golay United Kingdom | 55 | 8.2k 1.2× | 1.3k 0.8× | 2.5k 2.3× | 757 0.7× | 684 0.7× | 223 | 12.6k | ||
| Henrik Larsson Denmark | 60 | 8.0k 1.2× | 1.3k 0.8× | 1.4k 1.3× | 394 0.4× | 2.0k 2.0× | 305 | 14.6k | ||
| Mark E. Ladd Germany | 57 | 8.3k 1.2× | 919 0.6× | 885 0.8× | 1.4k 1.3× | 322 0.3× | 376 | 12.0k | ||
| Lothar R. Schad Germany | 56 | 8.4k 1.2× | 759 0.5× | 1.7k 1.5× | 1.8k 1.7× | 340 0.3× | 406 | 12.8k | ||
| Brian K. Rutt Canada | 57 | 6.6k 1.0× | 1.2k 0.7× | 952 0.9× | 726 0.7× | 398 0.4× | 216 | 11.8k | ||
| Pascal Spincemaille United States | 41 | 4.8k 0.7× | 745 0.5× | 847 0.8× | 784 0.8× | 324 0.3× | 174 | 6.5k | ||
| Jun Hatazawa Japan | 56 | 5.8k 0.9× | 2.4k 1.5× | 912 0.8× | 505 0.5× | 322 0.3× | 465 | 12.1k | ||
| Tian Liu United States | 46 | 5.1k 0.7× | 954 0.6× | 629 0.6× | 421 0.4× | 280 0.3× | 280 | 8.4k | ||
| Glyn Johnson United States | 51 | 7.6k 1.1× | 1.6k 0.9× | 421 0.4× | 332 0.3× | 1.3k 1.3× | 141 | 10.8k | ||
| Michael V. Knopp United States | 58 | 9.1k 1.3× | 941 0.6× | 523 0.5× | 379 0.4× | 731 0.7× | 358 | 14.0k |
Countries citing papers authored by Yi Wang
Since
Specialization
Citations
This map shows the geographic impact of Yi Wang'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 Yi Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yi Wang more than expected).
Fields of papers citing papers by Yi Wang
Since
Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences
This network shows the impact of papers produced by Yi Wang. 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 Yi Wang. The network helps show where Yi Wang may publish in the future.
Co-authorship network of co-authors of Yi Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Yi Wang. A scholar is included among the top collaborators of Yi Wang 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 Yi Wang. Yi Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
1.
Ran, Yan, et al.. (2025). Depressive symptoms trajectories and cardiovascular disease in Chinese middle-aged and older adults: A longitudinal cohort study. Journal of Affective Disorders. 380. 456–465.
2.
Hod, Eldad A., Christian Habeck, Alexey Dimov, et al.. (2025). Effects of iron repletion on brain iron content, myelination, neural network activation, and cognition. JCI Insight. 10(23).
3.
Luo, Hong, et al.. (2024). Chemical composition and discrimination with volatile profiles of Yongchuan Xiuya green tea with different baking treatments. Flavour and Fragrance Journal. 39(4). 224–235.
4.
Xu, Shaohua, et al.. (2023). A study on the detection of thyroid cancer in Hashimoto's thyroiditis using computed tomography imaging radiomics. Journal of Radiation Research and Applied Sciences. 16(4). 100677–100677.
5.
Zang, Ying, Jie Wang, Xiuhong Wu, et al.. (2023). The Analysis and Rapid Non-Destructive Evaluation of Yongchuan Xiuya Quality Based on NIRS Combined with Machine Learning Methods. Processes. 11(9). 2809–2809.
6.
Wang, Xiang, Jianying Zheng, Yi Wang, et al.. (2023). Vehicle Micro-Trajectory Automatic Acquisition Method Based on Multisensor Fusion. IEEE Sensors Journal. 23(18). 21506–21523.
7.
Zhao, Weiwei, Chunhui Yang, Luguang Chen, et al.. (2023). Relationship Between Iron Distribution in Deep Gray Matter Nuclei Measured by Quantitative Susceptibility Mapping and Motor Outcome After Deep Brain Stimulation in Patients With Parkinson's Disease. Journal of Magnetic Resonance Imaging. 58(2). 581–590.
8.
Yang, Linfeng, Junghun Cho, Kelly M. Gillen, et al.. (2022). Oxygen extraction fraction (OEF) assesses cerebral oxygen metabolism of deep gray matter in patients with pre-eclampsia. European Radiology. 32(9). 6058–6069.
9.
Zhang, Hang, et al.. (2022). IRIS—Intelligent Rapid Interactive Segmentation for Measuring Liver Cyst Volumes in Autosomal Dominant Polycystic Kidney Disease. Tomography. 8(1). 447–456.
10.
Chiang, Gloria, Junghun Cho, Jonathan P. Dyke, et al.. (2022). Brain oxygen extraction and neural tissue susceptibility are associated with cognitive impairment in older individuals. Journal of Neuroimaging. 32(4). 697–709.
11.
Li, Jing, Thanh D. Nguyen, Qihao Zhang, Lingfei Guo, & Yi Wang. (2022). Cerebral Microbleeds Are Associated With Increased Brain Iron and Cognitive Impairment in Patients With Cerebral Small Vessel Disease: A Quantitative Susceptibility Mapping Study. Journal of Magnetic Resonance Imaging. 56(3). 904–914.
12.
Jamison, Keith, Thanh D. Nguyen, Ulrike W. Kaunzner, et al.. (2021). Structural disconnectivity from paramagnetic rim lesions is related to disability in multiple sclerosis. Brain and Behavior. 11(10). e2353–e2353.
13.
Wang, Yi, et al.. (2020). Effects of solar radiation on thermal sensation and physical fatigue of the human body under heavy-load exercise. Indoor and Built Environment. 31(1). 7–16.
14.
Zhou, Liangdong, Qihao Zhang, Pascal Spincemaille, et al.. (2020). Quantitative transport mapping (QTM) of the kidney with an approximate microvascular network. Magnetic Resonance in Medicine. 85(4). 2247–2262.
15.
Deh, Kofi, Gerald Ponath, Kelly M. Gillen, et al.. (2018). Magnetic susceptibility increases as diamagnetic molecules breakdown: Myelin digestion during multiple sclerosis lesion formation contributes to increase on QSM. Journal of Magnetic Resonance Imaging. 48(5). 1281–1287.
16.
Chiang, Gloria, et al.. (2018). Quantitative Susceptibility Mapping of the Thalamus: Relationships with Thalamic Volume, Total Gray Matter Volume, and T2 Lesion Burden. American Journal of Neuroradiology. 39(3). 467–472.
17.
Yao, Yihao, Thanh D. Nguyen, Sneha Pandya, et al.. (2017). Combining Quantitative Susceptibility Mapping with Automatic Zero Reference (QSM0) and Myelin Water Fraction Imaging to Quantify Iron-Related Myelin Damage in Chronic Active MS Lesions. American Journal of Neuroradiology. 39(2). 303–310.
18.
Müller, Juliane, et al.. (2015). CH 4 parameter estimation in CLM4.5bgc using surrogate global optimization. Geoscientific model development. 8(10). 3285–3310.
19.
Pei, Mengchao, Thanh D. Nguyen, Nanda Deepa Thimmappa, et al.. (2014). Algorithm for fast monoexponential fitting based on Auto‐Regression on Linear Operations (ARLO) of data. Magnetic Resonance in Medicine. 73(2). 843–850.
20.
Zhang, Jingwei, Tian Liu, Ajay Gupta, et al.. (2014). Quantitative mapping of cerebral metabolic rate of oxygen (CMRO2) using quantitative susceptibility mapping (QSM). Magnetic Resonance in Medicine. 74(4). 945–952.
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.
Explore authors with similar magnitude of impact
Breakdown of academic impact, for papers by Xavier Golay Breakdown of academic impact, for papers by Henrik Larsson Breakdown of academic impact, for papers by Mark E. Ladd Breakdown of academic impact, for papers by Lothar R. Schad Breakdown of academic impact, for papers by Brian K. Rutt Breakdown of academic impact, for papers by Pascal Spincemaille Breakdown of academic impact, for papers by Jun Hatazawa Breakdown of academic impact, for papers by Tian Liu Breakdown of academic impact, for papers by Glyn Johnson Breakdown of academic impact, for papers by Michael V. Knopp