Qingfeng Wang
Impact in
- Polymers and Plastics top 10%
- Flame retardant materials and properties
- Synthesis and properties of polymers
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
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- COVID-19 diagnosis using AI 8
- Radiomics and Machine Learning in Medical Imaging 6
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- Lung Cancer Diagnosis and Treatment 10
- Co-authors
- Wenfang Shi (3 shared papers)Xuehai Zhou (9 shared papers)Changlong Li (7 shared papers)Jun Huang (20 shared papers)Jie‐Zhi Cheng (8 shared papers)Chao Wang (2 shared papers)Ying Zhou (5 shared papers)Qican Zhang (1 shared paper)
In The Last Decade
Qingfeng Wang
38 papers receiving 533 citations
Peers
Comparison fields: 5 of 101
- Polymers and Plastics 161
- Radiology, Nuclear Medicine and Imaging 123
- Computer Vision and Pattern Recognition 98
- Artificial Intelligence 86
- Computer Networks and Communications 58
Countries citing papers authored by Qingfeng Wang
This map shows the geographic impact of Qingfeng 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 Qingfeng Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qingfeng Wang more than expected).
Fields of papers citing papers by Qingfeng Wang
This network shows the impact of papers produced by Qingfeng 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 Qingfeng Wang. The network helps show where Qingfeng Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Qingfeng Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2006 | 99 | |
| 2 | 2019 | 79 | |
| 3 | 2005 | 55 | |
| 4 | 2018 | 52 | |
| 5 | 2006 | 42 | |
| 6 | 2017 | 30 | |
| 7 | 2020 | 27 | |
| 8 | 2010 | 27 | |
| 9 | 2017 | 24 | |
| 10 | 2023 | 16 | |
| 11 | 2010 | 10 | |
| 12 | 2019 | 8 | |
| 13 | 2018 | 7 | |
| 14 | 2019 | 7 | |
| 15 | 2020 | 6 | |
| 16 | 2018 | 6 | |
| 17 | 2019 | 5 | |
| 18 | 2017 | 5 | |
| 19 | 2024 | 4 | |
| 20 | 2020 | 4 |
About Qingfeng Wang
Qingfeng Wang is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Computer Vision and Pattern Recognition, Computational Mechanics and Artificial Intelligence, having authored 43 papers that have together received 548 indexed citations. Recurring topics across this work include Lung Cancer Diagnosis and Treatment (10 papers), COVID-19 diagnosis using AI (8 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), AI in cancer detection (4 papers), Model Reduction and Neural Networks (4 papers), Fluid Dynamics and Turbulent Flows (3 papers), Cloud Computing and Resource Management (3 papers) and Caching and Content Delivery (3 papers). The work is most often cited by research in Polymers and Plastics (161 citations), Radiology, Nuclear Medicine and Imaging (123 citations), Computer Vision and Pattern Recognition (98 citations), Artificial Intelligence (86 citations) and Computer Networks and Communications (58 citations). Qingfeng Wang has collaborated with scholars based in China, Taiwan and Singapore. Frequent co-authors include Wenfang Shi, Xuehai Zhou, Changlong Li, Jun Huang, Jie‐Zhi Cheng, Chao Wang, Ying Zhou, Qican Zhang, Xianyu Su and Qiyu Liu. Their work appears in journals such as Physics of Fluids, IEEE Access, Polymer Degradation and Stability, Scientific Reports and IEEE Transactions on Services Computing.
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.