Qunbo Wang
Impact in
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- Intensive Care Unit Cognitive Disorders
- Complementary and Manual Therapy top 10%
Papers in
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- Domain Adaptation and Few-Shot Learning 4
- Machine Learning and Algorithms 3
- Topic Modeling 2
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- Multimodal Machine Learning Applications 3
- Co-authors
- Gaohai Shao (4 shared papers)Bo Li (1 shared paper)Juan Wang (1 shared paper)Zhiwei Li (1 shared paper)Yu Yu (1 shared paper)Wenjun Wu (5 shared papers)Yu Yu (2 shared papers)Deyu Yang (1 shared paper)
In The Last Decade
Qunbo Wang
18 papers receiving 210 citations
Peers
Comparison fields: 5 of 74
- Critical Care and Intensive Care Medicine 43
- Complementary and Manual Therapy 10
- Developmental Neuroscience 14
- Anesthesiology and Pain Medicine 10
- Pathology and Forensic Medicine 23
Countries citing papers authored by Qunbo Wang
This map shows the geographic impact of Qunbo 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 Qunbo Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qunbo Wang more than expected).
Fields of papers citing papers by Qunbo Wang
This network shows the impact of papers produced by Qunbo 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 Qunbo Wang. The network helps show where Qunbo Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Qunbo 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 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 59 | |
| 2 | 2016 | 32 | |
| 3 | 2022 | 21 | |
| 4 | 2021 | 19 | |
| 5 | 2021 | 16 | |
| 6 | 2021 | 16 | |
| 7 | 2021 | 14 | |
| 8 | 2025 | 11 | |
| 9 | 2024 | 7 | |
| 10 | 2014 | 6 | |
| 11 | 2016 | 5 | |
| 12 | 2024 | 2 | |
| 13 | 2024 | 2 | |
| 14 | 2021 | 2 | |
| 15 | 2020 | 1 | |
| 16 | 2024 | 1 | |
| 17 | [Confidence high viscosity bone cement system and postural reduction in treating acute severe osteoporotic vertebral compression fractures]. | 2011 | 1 |
| 18 | 2024 | 1 | |
| 19 | 2024 | 0 | |
| 20 | 2025 | 0 |
About Qunbo Wang
Qunbo Wang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Complementary and Manual Therapy and Epidemiology, having authored 22 papers that have together received 216 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (4 papers), Machine Learning and Algorithms (3 papers), Multimodal Machine Learning Applications (3 papers), Therapeutic Uses of Natural Elements (2 papers), Myofascial pain diagnosis and treatment (2 papers), Fibromyalgia and Chronic Fatigue Syndrome Research (2 papers), Recommender Systems and Techniques (2 papers) and Topic Modeling (2 papers). The work is most often cited by research in Critical Care and Intensive Care Medicine (43 citations), Complementary and Manual Therapy (10 citations), Developmental Neuroscience (14 citations), Anesthesiology and Pain Medicine (10 citations) and Pathology and Forensic Medicine (23 citations). Qunbo Wang has collaborated with scholars based in China, Italy and Hong Kong. Frequent co-authors include Gaohai Shao, Bo Li, Juan Wang, Zhiwei Li, Yu Yu, Wenjun Wu, Yu Yu, Deyu Yang, Fu-Jun Luan and Hai‐Qiang Wang. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Neurocomputing, IEEE Robotics and Automation Letters, Annals of Palliative Medicine and ACM Transactions on Multimedia Computing Communications and Applications.
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.