Char Leung

747 citations
24 papers · 443 · h-index 8

Impact in

Papers in

    • SARS-CoV-2 and COVID-19 Research 5
    • COVID-19 Clinical Research Studies 4
    • Long-Term Effects of COVID-19 4
    • Peripheral Neuropathies and Disorders 3

Char Leung

17 papers receiving 431 citations

Peers

Char Leung
Comparison fields: 5 of 80
  • Modeling and Simulation 65
  • Infectious Diseases 174
  • Neurology 80
  • Obstetrics and Gynecology 36
  • Critical Care and Intensive Care Medicine 15
Replace Yanfang Ma with:
Yanfang Ma China
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Maryann M Bukelo Trinidad and Tobago
Niloufar Taherpour Iran
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Citations per field
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Citations per year

Countries citing papers authored by Char Leung

Since Specialization
Citations

This map shows the geographic impact of Char Leung'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 Char Leung with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Char Leung more than expected).

Fields of papers citing papers by Char Leung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Char Leung. 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 Char Leung. The network helps show where Char Leung may publish in the future.

Co-authors

The 10 scholars most cited alongside Char Leung, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Char Leung Line = papers co-authored together Char Leung links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020172
2 2020108
3 202064
4 202422
5 202018
6 202015
7 20239
8 20218
9 20206
10 20215
11 20223
12 20213
13 20193
14 20203
15 20242
16 20231
17 20191
18 20220
19 20240
20 20260

About Char Leung

Char Leung is a scholar working on Infectious Diseases, Neurology, Epidemiology, Obstetrics and Gynecology and Public Health, Environmental and Occupational Health, having authored 24 papers that have together received 443 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (5 papers), COVID-19 epidemiological studies (4 papers), COVID-19 Impact on Reproduction (4 papers), COVID-19 Clinical Research Studies (4 papers), Long-Term Effects of COVID-19 (4 papers), COVID-19 and healthcare impacts (3 papers), Peripheral Neuropathies and Disorders (3 papers) and Virology and Viral Diseases (2 papers). The work is most often cited by research in Modeling and Simulation (65 citations), Infectious Diseases (174 citations), Neurology (80 citations), Obstetrics and Gynecology (36 citations) and Critical Care and Intensive Care Medicine (15 citations). Char Leung has collaborated with scholars based in United Kingdom, Australia and Brazil. Frequent co-authors include Li Su, László Kónya, Karina Mary de Paiva, Ana Cristina Simões e Silva, Patrícia Haas, Pak‐Leung Ho, Eduardo A. Oliveira, Siddharth Sridhar, Munehito Machida and Jeremy Howick. Their work appears in journals such as Reviews in Medical Virology, Human Vaccines & Immunotherapeutics, Pacific Rim Property Research Journal, Pediatric Pulmonology and Pediatric Allergy and Immunology.

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.

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