WW Yan
Impact in
- Infectious Diseases top 1%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- Viral gastroenteritis research and epidemiology
- SARS-CoV-2 detection and testing
- Animal Science and Zoology top 1%
- Animal Virus Infections Studies
Papers in
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- Trauma, Hemostasis, Coagulopathy, Resuscitation 3
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- Acute Kidney Injury Research 4
- Co-authors
- Kwok‐Yung Yuen (3 shared papers)Rwh Yung (2 shared papers)Dnc Tsang (2 shared papers)John Malcolm Nicholls (2 shared papers)TK Ng (2 shared papers)KH Chan (1 shared paper)W. Lim (1 shared paper)Yi Guan (1 shared paper)
In The Last Decade
WW Yan
17 papers receiving 2.4k citations
WW Yan's Hit Papers
Peers
Comparison fields: 5 of 121
- Infectious Diseases 1.8k
- Animal Science and Zoology 542
- Modeling and Simulation 237
- Epidemiology 400
- Neurology 130
Countries citing papers authored by WW Yan
This map shows the geographic impact of WW Yan'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 WW Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites WW Yan more than expected).
Fields of papers citing papers by WW Yan
This network shows the impact of papers produced by WW Yan. 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 WW Yan. The network helps show where WW Yan may publish in the future.
Co-authors
The 25 scholars most cited alongside WW Yan, 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 | Coronavirus as a possible cause of severe acute respiratory syndrome Hit paper breakdown → | 2003 | 2409 |
| 2 | 2016 | 26 | |
| 3 | Clostridium perfringens liver abscess with massive haemolysis. | 2010 | 21 |
| 4 | Peiris JS, Lai ST, Poon LL, et al. Coronavirus as a possible cause of severe acute respiratory syndrome | 2003 | 15 |
| 5 | 2019 | 14 | |
| 6 | 2016 | 12 | |
| 7 | 2021 | 11 | |
| 8 | 2017 | 8 | |
| 9 | 2020 | 5 | |
| 10 | Hyperimmune intravenous immunoglobulin treatment: a multicentre double-blind randomised controlled trial for patients with severe A(H1N1)pdm09 Infection | 2014 | 3 |
| 11 | 2014 | 3 | |
| 12 | 2012 | 3 | |
| 13 | 2012 | 2 | |
| 14 | 2021 | 2 | |
| 15 | 2013 | 2 | |
| 16 | 2024 | 1 | |
| 17 | 2013 | 1 |
About WW Yan
WW Yan is a scholar working on Critical Care and Intensive Care Medicine, Nephrology, Epidemiology, Emergency Medicine and Pulmonary and Respiratory Medicine, having authored 17 papers that have together received 2.5k indexed citations. Recurring topics across this work include Sepsis Diagnosis and Treatment (7 papers), Acute Kidney Injury Research (4 papers), Trauma, Hemostasis, Coagulopathy, Resuscitation (3 papers), Pneumonia and Respiratory Infections (2 papers), Immune Response and Inflammation (2 papers), Poisoning and overdose treatments (1 paper), Heme Oxygenase-1 and Carbon Monoxide (1 paper) and Diabetic Foot Ulcer Assessment and Management (1 paper). The work is most often cited by research in Infectious Diseases (1.8k citations), Animal Science and Zoology (542 citations), Modeling and Simulation (237 citations), Epidemiology (400 citations) and Neurology (130 citations). WW Yan has collaborated with scholars based in China, Hong Kong and Belgium. Frequent co-authors include Kwok‐Yung Yuen, Rwh Yung, Dnc Tsang, John Malcolm Nicholls, TK Ng, KH Chan, W. Lim, Yi Guan, Hoi‐Ping Shum and Tak Mao Chan. Their work appears in journals such as Critical Care, The Lancet, F1000Research, Hong Kong Medical Journal and Indian Journal of Critical Care 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.