Che Kit Lin

986 citations
20 papers · 723 · h-index 14

Impact in

    • COVID-19 epidemiological studies
  • Epidemiology top 10%
    • Influenza Virus Research Studies
    • Hepatitis B Virus Studies
    • Respiratory viral infections research

Papers in

    • Influenza Virus Research Studies 4
    • Virology and Viral Diseases 1
    • Immune Cell Function and Interaction 5
    • Immunotherapy and Immune Responses 2

Che Kit Lin

20 papers receiving 701 citations

Peers

Che Kit Lin
Comparison fields: 5 of 82
  • Modeling and Simulation 104
  • Epidemiology 330
  • Infectious Diseases 116
  • Hepatology 46
  • Hematology 65
Replace Cheuk Kwong Lee with:
Cheuk Kwong Lee Hong Kong
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Xiucheng Pan China
Cynthia A. Mapua Philippines
Qirong Zhu China
Sandra Westhaus Germany
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Makhdum Ahmed United States
Yun Tian China
Babak Sayad Iran
Che Kit Lin relative to Cheuk Kwong Lee Hong Kong Cheuk Kwong Lee's profile →
Citations per field
00.5×1.5×2.1×
Cheuk Kwong Lee · 1×
Citations per year

Countries citing papers authored by Che Kit Lin

Since Specialization
Citations

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

Fields of papers citing papers by Che Kit Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Che Kit Lin. 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 Che Kit Lin. The network helps show where Che Kit Lin may publish in the future.

Co-authors

The 25 scholars most cited alongside Che Kit Lin, 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 Che Kit Lin Line = papers co-authored together Che Kit Lin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 2010155
2 201288
3 201173
4 200359
5 201152
6 200738
7 200236
8 201436
9 201035
10 200728
11 200725
12 200323
13 200621
14 200121
15 201512
16 19957
17 19906
18
A serial cross-sectional serologic survey of 2009 Pandemic (H1N1) in Hong Kong: implications for future pandemic influenza surveillance.
20114
19 20172
20 20012

About Che Kit Lin

Che Kit Lin is a scholar working on Epidemiology, Immunology, Oncology, Physiology and Infectious Diseases, having authored 20 papers that have together received 723 indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (5 papers), Influenza Virus Research Studies (4 papers), Viral-associated cancers and disorders (3 papers), Blood groups and transfusion (2 papers), Blood donation and transfusion practices (2 papers), Immunotherapy and Immune Responses (2 papers), Erythrocyte Function and Pathophysiology (2 papers) and Virology and Viral Diseases (1 paper). The work is most often cited by research in Modeling and Simulation (104 citations), Epidemiology (330 citations), Infectious Diseases (116 citations), Hepatology (46 citations) and Hematology (65 citations). Che Kit Lin has collaborated with scholars based in Hong Kong, China and United Kingdom. Frequent co-authors include Ivan Fan‐Ngai Hung, Joseph T. Wu, YL Lau, Malik Peiris, Daniel K. W. Chu, Cheuk Kwong Lee, Benjamin J. Cowling, GM Leung, Su‐Vui Lo and Clement K. M. Leung. Their work appears in journals such as American Journal of Clinical Pathology, Transfusion, Journal of Virology, Environmental Science and Pollution Research and Journal of Clinical Pathology.

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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