Wei He
Impact in
- Infectious Diseases top 2%
- COVID-19 Clinical Research Studies
- SARS-CoV-2 and COVID-19 Research
- Modeling and Simulation top 2%
Papers in
- Epidemiology 16
- Congenital Heart Disease Studies 6
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- Cardiovascular Function and Risk Factors 4
- Co-authors
- Peng Bai (2 shared papers)Fei Wu (2 shared papers)Jin‐Kui Yang (2 shared papers)Shi Liu (2 shared papers)Jianmin Jin (2 shared papers)De-min Han (1 shared paper)Xiaofang Liu (1 shared paper)Steven J. Atlas (10 shared papers)
- Journals
- PLoS ONE (5 papers)Journal of General Internal Medicine (5 papers)Medicine (2 papers)The Journal of Clinical Endocrinology & Metabolism (2 papers)Frontiers in Public Health (2 papers)
- Partner nations
- ChinaUnited StatesTaiwan
In The Last Decade
Wei He
102 papers receiving 3.3k citations
Wei He's Hit Papers
Peers
Comparison fields: 5 of 159
- Infectious Diseases 830
- Modeling and Simulation 154
- Parasitology 172
- Obstetrics and Gynecology 176
- Neurology 274
Countries citing papers authored by Wei He
This map shows the geographic impact of Wei He'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 Wei He with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wei He more than expected).
Fields of papers citing papers by Wei He
This network shows the impact of papers produced by Wei He. 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 Wei He. The network helps show where Wei He may publish in the future.
Co-authors
The 25 scholars most cited alongside Wei He, 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 109 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Gender Differences in Patients With COVID-19: Focus on Severity and Mortality Hit paper breakdown → | 2020 | 1452 |
| 2 | 1994 | 262 | |
| 3 | 2015 | 109 | |
| 4 | 2021 | 75 | |
| 5 | 2020 | 63 | |
| 6 | 2020 | 63 | |
| 7 | 2021 | 55 | |
| 8 | 2012 | 52 | |
| 9 | 1994 | 49 | |
| 10 | 2002 | 48 | |
| 11 | 2014 | 48 | |
| 12 | 2011 | 46 | |
| 13 | 2020 | 44 | |
| 14 | 2005 | 39 | |
| 15 | 2015 | 37 | |
| 16 | 2014 | 37 | |
| 17 | 2020 | 36 | |
| 18 | 2005 | 35 | |
| 19 | 2016 | 32 | |
| 20 | 2019 | 31 |
About Wei He
Wei He is a scholar working on Epidemiology, Cardiology and Cardiovascular Medicine, Parasitology, Infectious Diseases and Oncology, having authored 109 papers that have together received 3.4k indexed citations. Recurring topics across this work include Parasites and Host Interactions (9 papers), Congenital Heart Disease Studies (6 papers), COVID-19 Clinical Research Studies (5 papers), Cardiovascular Function and Risk Factors (4 papers), Colorectal Cancer Screening and Detection (4 papers), Ultrasound in Clinical Applications (4 papers), Stress Responses and Cortisol (3 papers) and Helminth infection and control (3 papers). The work is most often cited by research in Infectious Diseases (830 citations), Modeling and Simulation (154 citations), Parasitology (172 citations), Obstetrics and Gynecology (176 citations) and Neurology (274 citations). Wei He has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Peng Bai, Fei Wu, Jin‐Kui Yang, Shi Liu, Jianmin Jin, De-min Han, Xiaofang Liu, Steven J. Atlas, Patricia K. Donahoe and Michael L. Gustafson. Their work appears in journals such as PLoS ONE, Journal of General Internal Medicine, Medicine, The Journal of Clinical Endocrinology & Metabolism and Frontiers in Public Health.
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.