Meiyun Wang

4.1k total citations · 1 hit paper
52 papers, 2.6k citations indexed

About

Meiyun Wang is a scholar working on Radiology, Nuclear Medicine and Imaging, Infectious Diseases and Health. According to data from OpenAlex, Meiyun Wang has authored 52 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Radiology, Nuclear Medicine and Imaging, 10 papers in Infectious Diseases and 9 papers in Health. Recurrent topics in Meiyun Wang's work include Radiomics and Machine Learning in Medical Imaging (21 papers), SARS-CoV-2 and COVID-19 Research (10 papers) and MRI in cancer diagnosis (10 papers). Meiyun Wang is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (21 papers), SARS-CoV-2 and COVID-19 Research (10 papers) and MRI in cancer diagnosis (10 papers). Meiyun Wang collaborates with scholars based in China, United States and Tanzania. Meiyun Wang's co-authors include Zhenyu Liu, Jie Tian, Kai Sun, Di Dong, Xuezhi Zhou, Longfei Li, Jingwei Wei, Shuo Wang, Bo Li and Cheng Fang and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and NeuroImage.

In The Last Decade

Meiyun Wang

48 papers receiving 2.5k citations

Hit Papers

The Applications of Radio... 2019 2026 2021 2023 2019 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Meiyun Wang China 21 1.7k 481 422 392 391 52 2.6k
Roger Sun France 19 1.7k 1.0× 706 1.5× 236 0.6× 792 2.0× 413 1.1× 67 2.3k
Ulrike Schick France 30 1.8k 1.1× 1.4k 2.8× 206 0.5× 732 1.9× 415 1.1× 189 3.1k
Stephanie Tanadini‐Lang Switzerland 36 3.0k 1.8× 2.1k 4.3× 317 0.8× 599 1.5× 812 2.1× 163 4.7k
Zhaoxiang Ye China 29 2.6k 1.6× 1.7k 3.6× 400 0.9× 544 1.4× 520 1.3× 190 3.4k
Kaustav Bera United States 25 2.7k 1.6× 1.1k 2.2× 1.0k 2.4× 904 2.3× 563 1.4× 91 3.7k
Tamim Niazi Canada 23 750 0.5× 734 1.5× 187 0.4× 359 0.9× 130 0.3× 118 1.6k
Luca Boldrini Italy 32 2.4k 1.5× 1.1k 2.4× 238 0.6× 845 2.2× 600 1.5× 235 3.6k
Carlos Cárdenas United States 26 1.3k 0.8× 553 1.1× 336 0.8× 208 0.5× 441 1.1× 134 2.3k
Stefano Trebeschi Netherlands 16 1.1k 0.7× 370 0.8× 201 0.5× 534 1.4× 318 0.8× 47 1.5k
Corinne Balleyguier France 39 2.1k 1.2× 1.4k 2.9× 779 1.8× 1.0k 2.7× 736 1.9× 183 4.9k

Countries citing papers authored by Meiyun Wang

Since Specialization
Citations

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

Fields of papers citing papers by Meiyun Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Meiyun Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Meiyun Wang. A scholar is included among the top collaborators of Meiyun 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 Meiyun Wang. Meiyun Wang 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.
Dahmani, Louisa, Yan Bai, Wei Zhang, et al.. (2025). Individualized functional connectivity markers for motor and mood symptoms of Parkinson’s disease. NeuroImage. 324. 121631–121631.
2.
Wang, Yubo, et al.. (2025). Leveraging machine learning with dynamic 18F-FDG PET/CT: integrating metabolic and flow features for lung cancer differential diagnosis. European Journal of Nuclear Medicine and Molecular Imaging. 52(10). 3807–3819. 1 indexed citations
3.
Yu, Xuan, Jing Zhou, Yaping Wu, et al.. (2024). Assessment of MGMT promoter methylation status in glioblastoma using deep learning features from multi-sequence MRI of intratumoral and peritumoral regions. Cancer Imaging. 24(1). 172–172. 9 indexed citations
4.
Miao, Yudong, Quanman Li, Dongyang Xu, et al.. (2024). Understanding the impact of chronic diseases on COVID‐19 vaccine hesitancy using propensity score matching: Internet‐based cross‐sectional study. Journal of Clinical Nursing. 33(6). 2165–2177. 3 indexed citations
6.
Wang, Meiyun, Kiyoshi Izumi, & Hiroki Sakaji. (2024). LLMFactor: Extracting Profitable Factors through Prompts for Explainable Stock Movement Prediction. 3120–3131. 6 indexed citations
7.
Li, Jie, Tingting Bai, Wenxuan Hu, et al.. (2024). Geochemical properties and mineralization of thorium. 18. 100081–100081. 2 indexed citations
8.
Wei, Wei, et al.. (2024). Abnormal static and dynamic brain network connectivity associated with chronic tinnitus. Neuroscience. 554. 26–33. 2 indexed citations
9.
Wu, Jian, Xinghong Guo, Meiyun Wang, et al.. (2023). The pattern from the first three rounds of vaccination: declining vaccination rates. Frontiers in Public Health. 11. 1124548–1124548. 2 indexed citations
10.
11.
Wu, Jian, Quanman Li, Clifford Silver Tarimo, et al.. (2023). How urban versus rural residency relates to COVID-19 vaccine hesitancy: A large-scale national Chinese study. Social Science & Medicine. 320. 115695–115695. 27 indexed citations
12.
Wu, Jian, Yudong Miao, Quanman Li, et al.. (2022). COVID-19 Vaccination Acceptance Among Chinese Population and Its Implications for the Pandemic: A National Cross-Sectional Study. Frontiers in Public Health. 10. 796467–796467. 16 indexed citations
13.
Wu, Jian, Quanman Li, Clifford Silver Tarimo, et al.. (2021). COVID-19 Vaccine Hesitancy Among Chinese Population: A Large-Scale National Study. Frontiers in Immunology. 12. 781161–781161. 91 indexed citations
14.
Wu, Qingxia, Shuo Wang, Yan Wang, et al.. (2019). Radiomics analysis of magnetic resonance imaging improves diagnostic performance of lymph node metastasis in patients with cervical cancer. Radiotherapy and Oncology. 138. 141–148. 85 indexed citations
15.
Wang, Meiyun, Xiubo Jiang, Wenlong Wu, & Dongfeng Zhang. (2013). A meta-analysis of alcohol consumption and the risk of gout. Clinical Rheumatology. 32(11). 1641–1648. 62 indexed citations
16.
Sorensen, A. Gregory, Kyrre E. Emblem, Pavlina Polaskova, et al.. (2011). Increased Survival of Glioblastoma Patients Who Respond to Antiangiogenic Therapy with Elevated Blood Perfusion. Cancer Research. 72(2). 402–407. 241 indexed citations
17.
Sorensen, A. Gregory, Tracy T. Batchelor, Weiting Zhang, et al.. (2009). A “Vascular Normalization Index” as Potential Mechanistic Biomarker to Predict Survival after a Single Dose of Cediranib in Recurrent Glioblastoma Patients. Cancer Research. 69(13). 5296–5300. 291 indexed citations
18.
Dong, Zhiqiang, et al.. (2006). The Compensatory Mechanism in Exploring Crop Production Potential. ACTA AGRONOMICA SINICA. 32(10). 1566–1573. 20 indexed citations
19.
Wang, Meiyun, et al.. (2004). Synchrony of Double-ear Development of Forage Maize in Cold Upland. ACTA AGRONOMICA SINICA. 30(4). 388–392. 1 indexed citations
20.
Li, Shaokun, et al.. (1999). Cluster analysis for photosynthetic characters of inbred lines of maize in China. Zuo wu xue bao. 25(6). 733–741. 3 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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