Che Kit Lin
Impact in
- Modeling and Simulation top 2%
- 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
- Co-authors
- Ivan Fan‐Ngai Hung (5 shared papers)YL Lau (4 shared papers)GM Leung (4 shared papers)Cheuk Kwong Lee (3 shared papers)Joseph T. Wu (4 shared papers)Benjamin J. Cowling (4 shared papers)Su‐Vui Lo (4 shared papers)Daniel K. W. Chu (4 shared papers)
- Journals
- American Journal of Clinical Pathology (2 papers)Transfusion (2 papers)Genes and Immunity (1 paper)Transfusion Medicine (1 paper)Cancer Immunology Immunotherapy (1 paper)
- Partner nations
- Hong KongChinaUnited Kingdom
In The Last Decade
Che Kit Lin
20 papers receiving 681 citations
Peers
Comparison fields: 5 of 80
- Modeling and Simulation 100
- Epidemiology 323
- Infectious Diseases 113
- Hepatology 44
- Hematology 62
Countries citing papers authored by Che Kit Lin
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
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.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 150 | |
| 2 | 2012 | 86 | |
| 3 | 2011 | 71 | |
| 4 | 2003 | 58 | |
| 5 | 2011 | 50 | |
| 6 | 2007 | 37 | |
| 7 | 2014 | 36 | |
| 8 | 2010 | 34 | |
| 9 | 2002 | 33 | |
| 10 | 2007 | 28 | |
| 11 | 2007 | 24 | |
| 12 | 2003 | 22 | |
| 13 | 2001 | 21 | |
| 14 | 2006 | 19 | |
| 15 | 2015 | 11 | |
| 16 | 1995 | 6 | |
| 17 | 1990 | 6 | |
| 18 | A serial cross-sectional serologic survey of 2009 Pandemic (H1N1) in Hong Kong: implications for future pandemic influenza surveillance. | 2011 | 4 |
| 19 | 2017 | 2 | |
| 20 | 2001 | 2 |
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 700 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 (100 citations), Epidemiology (323 citations), Infectious Diseases (113 citations), Hepatology (44 citations) and Hematology (62 citations). Che Kit Lin has collaborated with scholars based in Hong Kong, China and United Kingdom. Frequent co-authors include Ivan Fan‐Ngai Hung, YL Lau, GM Leung, Cheuk Kwong Lee, Joseph T. Wu, Benjamin J. Cowling, Su‐Vui Lo, Daniel K. W. Chu, Malik Peiris and Clement K. M. Leung. Their work appears in journals such as American Journal of Clinical Pathology, Transfusion, Genes and Immunity, Transfusion Medicine and Cancer Immunology Immunotherapy.
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.