Meiyun Wang
- Radiology, Nuclear Medicine and Imaging top 0.5%
- Pulmonary and Respiratory Medicine top 5%
- Artificial Intelligence top 5%
- Oncology top 10%
- Biomedical Engineering top 10%
- Co-authors
- Zhenyu LiuJie TianKai SunDi DongJingwei WeiLongfei LiShuo WangCheng Fang
- Topics
- Radiomics and Machine Learning in Medical Imaging (21 papers)SARS-CoV-2 and COVID-19 Research (10 papers)MRI in cancer diagnosis (10 papers)
- Journals
- Nature CommunicationsSHILAP Revista de lepidopterologíaNeuroImage
- Partner nations
- ChinaUnited StatesTanzania
In The Last Decade
Meiyun Wang
48 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 124
- Radiology, Nuclear Medicine and Imaging 1.7k
- Pulmonary and Respiratory Medicine 481
- Artificial Intelligence 422
- Oncology 392
- Biomedical Engineering 391
Countries citing papers authored by Meiyun Wang
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
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
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 6 | |
| 4 | 3 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | 27 | |
| 8 | 2 | |
| 9 | 7 | |
| 10 | 6 | |
| 11 | 91 | |
| 12 | 36 | |
| 13 | 85 | |
| 14 | 123 | |
| 15 | 5 | |
| 16 | 241 | |
| 17 | 291 | |
| 18 | The Compensatory Mechanism in Exploring Crop Production Potential | 20 |
| 19 | Synchrony of Double-ear Development of Forage Maize in Cold Upland | 1 |
| 20 | Cluster analysis for photosynthetic characters of inbred lines of maize in China | 3 |
About Meiyun Wang
Meiyun Wang is a scholar working on Modeling and Simulation, Radiology, Nuclear Medicine and Imaging and Health, having authored 52 papers that have together received 2.6k indexed citations. Recurring topics across this 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). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (1.7k citations), Health Informatics (72 citations) and Obstetrics and Gynecology (226 citations). Meiyun Wang has collaborated with scholars based in China, United States and Tanzania. Frequent co-authors include Zhenyu Liu, Jie Tian, Kai Sun, Di Dong, Jingwei Wei, Longfei Li, Shuo Wang, Cheng Fang, Xuezhi Zhou and Bo Li. Their work appears in journals such as Nature Communications, SHILAP Revista de lepidopterología and NeuroImage.
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.