Kun Xia
Impact in
- Rehabilitation top 5%
- Wound Healing and Treatments
- Cancer Research top 10%
- MicroRNA in disease regulation
Papers in
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- Human Pose and Action Recognition 6
- Multimodal Machine Learning Applications 3
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- Cardiac Health and Mental Health 3
- Co-authors
- Jinzhuo Wang (1 shared paper)Le Wang (6 shared papers)Wei Tang (4 shared papers)Sanpin Zhou (7 shared papers)Xiaodong Ju (1 shared paper)Weiguo Wang (1 shared paper)Si‐quan Lou (1 shared paper)Jiahui Xia (1 shared paper)
- Journals
- Theranostics (3 papers)BMC Cardiovascular Disorders (2 papers)Advanced Science (2 papers)Coronary Artery Disease (1 paper)Molecular Medicine (1 paper)
- Partner nations
- ChinaUnited StatesFrance
In The Last Decade
Kun Xia
50 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 127
- Rehabilitation 100
- Cancer Research 181
- Orthopedics and Sports Medicine 89
- Genetics 97
- Microbiology 47
Countries citing papers authored by Kun Xia
This map shows the geographic impact of Kun Xia'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 Kun Xia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kun Xia more than expected).
Fields of papers citing papers by Kun Xia
This network shows the impact of papers produced by Kun Xia. 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 Kun Xia. The network helps show where Kun Xia may publish in the future.
Co-authors
The 25 scholars most cited alongside Kun Xia, 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 55 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 207 | |
| 2 | 2020 | 179 | |
| 3 | 2020 | 132 | |
| 4 | 2020 | 130 | |
| 5 | 2019 | 99 | |
| 6 | 2021 | 95 | |
| 7 | 2019 | 63 | |
| 8 | 2003 | 58 | |
| 9 | 2020 | 52 | |
| 10 | 2020 | 47 | |
| 11 | 2019 | 45 | |
| 12 | 2023 | 38 | |
| 13 | 2022 | 37 | |
| 14 | 2020 | 30 | |
| 15 | [Effects of intracoronary or intravenous tirofiban administration in patients with acute ST-elevation myocardial infarction undergoing primary percutaneous coronary intervention]. | 2007 | 24 |
| 16 | 2019 | 20 | |
| 17 | 2022 | 18 | |
| 18 | 2008 | 14 | |
| 19 | 2023 | 13 | |
| 20 | 2021 | 13 |
About Kun Xia
Kun Xia is a scholar working on Computer Vision and Pattern Recognition, Cardiology and Cardiovascular Medicine, Artificial Intelligence, Urology and Rehabilitation, having authored 55 papers that have together received 1.4k indexed citations. Recurring topics across this work include Human Pose and Action Recognition (6 papers), Anomaly Detection Techniques and Applications (5 papers), Extracellular vesicles in disease (4 papers), Multimodal Machine Learning Applications (3 papers), Graphene and Nanomaterials Applications (3 papers), Coronary Interventions and Diagnostics (3 papers), Cardiac Health and Mental Health (3 papers) and MicroRNA in disease regulation (2 papers). The work is most often cited by research in Rehabilitation (100 citations), Cancer Research (181 citations), Orthopedics and Sports Medicine (89 citations), Genetics (97 citations) and Microbiology (47 citations). Kun Xia has collaborated with scholars based in China, United States and France. Frequent co-authors include Jinzhuo Wang, Le Wang, Wei Tang, Sanpin Zhou, Xiaodong Ju, Weiguo Wang, Si‐quan Lou, Jiahui Xia, Zhen‐Xing Wang and Lefeng Wang. Their work appears in journals such as Theranostics, BMC Cardiovascular Disorders, Advanced Science, Coronary Artery Disease and Molecular Medicine.
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.