Xiaoxin Wu
Impact in
- Infectious Diseases top 1%
- COVID-19 Clinical Research Studies
- SARS-CoV-2 and COVID-19 Research
- Neurology top 2%
- Long-Term Effects of COVID-19
Papers in ⓘ
-
- SARS-CoV-2 and COVID-19 Research 9
- COVID-19 Clinical Research Studies 7
- Co-authors
- Lanjuan Li (25 shared papers)Hainv Gao (4 shared papers)Xiaowei Xu (6 shared papers)Yunqing Qiu (2 shared papers)Kaijin Xu (3 shared papers)Jifang Sheng (3 shared papers)Huaying Wang (1 shared paper)Lingjun Ying (1 shared paper)
- Journals
- Medicine (6 papers)BMC Infectious Diseases (4 papers)Cellular Physiology and Biochemistry (3 papers)Virology Journal (3 papers)Scientific Reports (2 papers)
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Xiaoxin Wu
80 papers receiving 2.4k citations
Hit Papers
Peers
Comparison fields: 5 of 149
- Infectious Diseases 1.3k
- Neurology 678
- Modeling and Simulation 141
- Epidemiology 486
- Geriatrics and Gerontology 51
Countries citing papers authored by Xiaoxin Wu
This map shows the geographic impact of Xiaoxin 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 Xiaoxin Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaoxin Wu more than expected).
Fields of papers citing papers by Xiaoxin Wu
This network shows the impact of papers produced by Xiaoxin 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 Xiaoxin Wu. The network helps show where Xiaoxin Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Xiaoxin 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
Showing the 20 most-cited of 87 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Clinical findings in a group of patients infected with the 2019 novel coronavirus (SARS-Cov-2) outside of Wuhan, China: retrospective case series Hit paper breakdown → | 2020 | 1497 |
| 2 | 2010 | 123 | |
| 3 | 2020 | 84 | |
| 4 | 2016 | 63 | |
| 5 | 2015 | 44 | |
| 6 | 2023 | 34 | |
| 7 | 2015 | 33 | |
| 8 | 2016 | 31 | |
| 9 | 2020 | 29 | |
| 10 | 2017 | 29 | |
| 11 | 2020 | 27 | |
| 12 | 2018 | 26 | |
| 13 | 2015 | 25 | |
| 14 | 2021 | 23 | |
| 15 | 2021 | 21 | |
| 16 | 2017 | 18 | |
| 17 | 2016 | 17 | |
| 18 | 2020 | 17 | |
| 19 | 2023 | 15 | |
| 20 | 2021 | 15 |
About Xiaoxin Wu
Xiaoxin Wu is a scholar working on Microbiology, Infectious Diseases, Epidemiology, Hepatology and Neurology, having authored 87 papers that have together received 2.5k indexed citations. Recurring topics across this work include Influenza Virus Research Studies (19 papers), SARS-CoV-2 and COVID-19 Research (9 papers), Liver Disease Diagnosis and Treatment (8 papers), Respiratory viral infections research (8 papers), Hepatitis B Virus Studies (7 papers), COVID-19 Clinical Research Studies (7 papers), Animal Disease Management and Epidemiology (6 papers) and Moyamoya disease diagnosis and treatment (5 papers). The work is most often cited by research in Infectious Diseases (1.3k citations), Neurology (678 citations), Modeling and Simulation (141 citations), Epidemiology (486 citations) and Geriatrics and Gerontology (51 citations). Xiaoxin Wu has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Lanjuan Li, Hainv Gao, Xiaowei Xu, Yunqing Qiu, Kaijin Xu, Jifang Sheng, Huaying Wang, Lingjun Ying, Hongliu Cai and Sheng Zhang. Their work appears in journals such as Medicine, BMC Infectious Diseases, Cellular Physiology and Biochemistry, Virology Journal and Scientific Reports.
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.