Pei Hua Lee

2.4k citations
13 papers · 515 indexed · 1 hit paper · h-index 7
Topics
SARS-CoV-2 and COVID-19 Research (6 papers)COVID-19 Clinical Research Studies (5 papers)COVID-19 epidemiological studies (2 papers)

In The Last Decade

Pei Hua Lee

11 papers receiving 509 citations

Hit Papers

Clinical and Virological Features of Severe Acute Respira...2021202620222024202150100150200250

Peers

Pei Hua Lee
Comparison fields: 5 of 63
  • Infectious Diseases 401
  • Modeling and Simulation 78
  • Epidemiology 69
  • Neurology 67
  • Radiology, Nuclear Medicine and Imaging 59
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Shinae Yu South Korea
Paul G. Carty Ireland
Ali Nizar Latif Qatar
Dong Wei China
Anvar Hassan Kaleeckal Qatar
Aifang Xu China
Zhongtao Gai China
Ga Eun Park South Korea
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Pei Hua Lee relative to Shinae Yu South Korea Shinae Yu's profile →
Citations per field
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Shinae Yu · 1×
Citations per year

Countries citing papers authored by Pei Hua Lee

Since Specialization
Citations

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

Fields of papers citing papers by Pei Hua Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pei Hua Lee. 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 Pei Hua Lee. The network helps show where Pei Hua Lee may publish in the future.

Co-authorship network of co-authors of Pei Hua Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Pei Hua Lee. A scholar is included among the top collaborators of Pei Hua Lee based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Pei Hua Lee. Pei Hua Lee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

13 of 13 papers shown
#WorkIndexed citations
1 0
2 0
3 6
4 14
5 4
6
Clinical and Virological Features of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Variants of Concern: A Retrospective Cohort Study Comparing B.1.1.7 (Alpha), B.1.351 (Beta), and B.1.617.2 (Delta)breakdown →
263
7 49
8 95
9 24
10 27
11 3
12 2
13 28

About Pei Hua Lee

Pei Hua Lee is a scholar working on Infectious Diseases, Modeling and Simulation and Obstetrics and Gynecology, having authored 13 papers that have together received 515 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (6 papers), COVID-19 Clinical Research Studies (5 papers) and COVID-19 epidemiological studies (2 papers). The work is most often cited by research in Infectious Diseases (401 citations), Modeling and Simulation (78 citations) and Health Informatics (7 citations). Pei Hua Lee has collaborated with scholars based in Singapore, Taiwan and United Kingdom. Frequent co-authors include Sean Wei Xiang Ong, Barnaby Edward Young, David Chien Lye, Yee‐Sin Leo, Tau Hong Lee, Matthias Paul HS Toh, Li Wei Ang, Tze Minn Mak, Po Ying Chia and Vernon J. Lee. Their work appears in journals such as PLoS ONE, Clinical Infectious Diseases and Clinical Microbiology and Infection.

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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