Xiaojun Wu
- Neurology top 5%
- Long-Term Effects of COVID-19 5
- Infectious Diseases top 5%
- COVID-19 Clinical Research Studies 5
- SARS-CoV-2 and COVID-19 Research 3
- Endocrinology top 10%
- Vibrio bacteria research studies 3
- Escherichia coli research studies 3
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- Salmonella and Campylobacter epidemiology 4
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- Pneumonia and Respiratory Infections 4
- Respiratory viral infections research 3
- Co-authors
- Hanxiang NieRuiyun LiXuhong DingYi HuLu YangYihua WangYilu ZhouRob M. Ewing
- Journals
- Cancer Research (2 papers)BMC Infectious Diseases (2 papers)American Journal of Clinical Pathology (2 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Xiaojun Wu
30 papers receiving 773 citations
Hit Papers
Peers
Comparison fields: 5 of 90
- Neurology 434
- Critical Care and Intensive Care Medicine 121
- Infectious Diseases 343
- Endocrinology 44
- Pulmonary and Respiratory Medicine 238
Countries citing papers authored by Xiaojun Wu
This map shows the geographic impact of Xiaojun Wu'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 Xiaojun Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaojun Wu more than expected).
Fields of papers citing papers by Xiaojun Wu
This network shows the impact of papers produced by Xiaojun Wu. 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 Xiaojun Wu. The network helps show where Xiaojun Wu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Xiaojun Wu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 2 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 5 | |
| 4 | 2023 | 9 | |
| 5 | 2022 | 10 | |
| 6 | 2022 | 2 | |
| 7 | 2022 | 5 | |
| 8 | 3-month, 6-month, 9-month, and 12-month respiratory outcomes in patients following COVID-19-related hospitalisation: a prospective studybreakdown → | 2021 | 433 |
| 9 | 2021 | 6 | |
| 10 | 2020 | 77 | |
| 11 | 2020 | 24 | |
| 12 | 2020 | 4 | |
| 13 | 2019 | 11 | |
| 14 | 2019 | 21 | |
| 15 | 2018 | 2 | |
| 16 | 2016 | 12 | |
| 17 | 2016 | 7 | |
| 18 | 2015 | 5 | |
| 19 | 2014 | 23 | |
| 20 | 2006 | 3 |
About Xiaojun Wu
Xiaojun Wu is a scholar working on Endocrinology, Infectious Diseases and Molecular Medicine, having authored 31 papers that have together received 784 indexed citations. Recurring topics across this work include COVID-19 Clinical Research Studies (5 papers), Long-Term Effects of COVID-19 (5 papers), Salmonella and Campylobacter epidemiology (4 papers), Pneumonia and Respiratory Infections (4 papers), SARS-CoV-2 and COVID-19 Research (3 papers), Vibrio bacteria research studies (3 papers), Escherichia coli research studies (3 papers) and Respiratory viral infections research (3 papers). The work is most often cited by research in Neurology (434 citations), Critical Care and Intensive Care Medicine (121 citations) and Infectious Diseases (343 citations). Xiaojun Wu has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Hanxiang Nie, Ruiyun Li, Xuhong Ding, Yi Hu, Lu Yang, Yihua Wang, Yilu Zhou, Rob M. Ewing, Fang Ni and Si Fang. Their work appears in journals such as Cancer Research, BMC Infectious Diseases, American Journal of Clinical Pathology, Scientific Reports and Microbiology.
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.