Meiyun Wang

10.0k citations
148 papers · 6.2k indexed · 1 hit paper · h-index 33

Impact in

Papers in

Meiyun Wang

136 papers receiving 6.1k citations

Hit Papers

Presumed Asymptomatic Carrier Transmission of COVID-19 2020 · 3.0k citations
3.0k202020262022202410002.0k3.0k

Peers

Meiyun Wang
Comparison fields: 5 of 191
  • Modeling and Simulation 833
  • Health Informatics 143
  • Radiology, Nuclear Medicine and Imaging 2.2k
  • Infectious Diseases 1.7k
  • General Dentistry 117
Replace Yan Bai with:
Yan Bai China
Chuansheng Zheng China
Long Jiang Zhang China
Andrea Remuzzi Italy
Stefania Boccia Italy
Xiaolong Qi China
Jianxing He China
Chen Wang China
Weimin Li China
Lei Shi China
Meiyun Wang relative to Yan Bai China Yan Bai's profile →
Citations per field
00.5×20×40×60×78×
Yan Bai · 1×
Citations per year

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-authors

The 25 scholars most cited alongside Meiyun Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Meiyun Wang Line = papers co-authored together Meiyun Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20245
3 20240
4 20242
5 20245
6 202378
7 202313
8 202311
9 202312
10 20238
11 202127
12 202142
13 202049
14 20194
15 20196
16 201519
17 201414
18 201346
19 20112
20 201123

About Meiyun Wang

Meiyun Wang is a scholar working on Radiology, Nuclear Medicine and Imaging, Health Informatics, Neurology, Hepatology and Genetics, having authored 148 papers that have together received 6.2k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (49 papers), Medical Imaging Techniques and Applications (30 papers), MRI in cancer diagnosis (27 papers), Advanced MRI Techniques and Applications (19 papers), Advanced X-ray and CT Imaging (13 papers), Medical Image Segmentation Techniques (11 papers), AI in cancer detection (9 papers) and Brain Tumor Detection and Classification (9 papers). The work is most often cited by research in Modeling and Simulation (833 citations), Health Informatics (143 citations), Radiology, Nuclear Medicine and Imaging (2.2k citations), Infectious Diseases (1.7k citations) and General Dentistry (117 citations). Meiyun Wang has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Yan Bai, Fei Tian, Dong‐Yan Jin, Lijuan Chen, Tao Wei, Dapeng Shi, Jie Tian, Yaping Wu, Yusong Lin and Qingxia Wu. Their work appears in journals such as European Radiology, European Journal of Nuclear Medicine and Molecular Imaging, IEEE Journal of Biomedical and Health Informatics, Frontiers in Oncology and Medical Physics.

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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