Cuiting Luo

2.7k citations
18 papers · 575 · 1 hit paper · h-index 8

Impact in

    • SARS-CoV-2 and COVID-19 Research
    • COVID-19 Clinical Research Studies
    • Viral gastroenteritis research and epidemiology
    • SARS-CoV-2 detection and testing
    • COVID-19 epidemiological studies

Papers in

Cuiting Luo

17 papers receiving 568 citations

Cuiting Luo's Hit Papers

Surgical Mask Partition Reduces the Risk of Noncontact Transmission in a Golden Syrian Hamster Model for Coronavirus Disease 2019 (COVID-19) 2020 · 400 citations
4000+2+4Years since publication100200300400

Peers

Cuiting Luo
Comparison fields: 5 of 96
  • Infectious Diseases 365
  • Modeling and Simulation 70
  • Animal Science and Zoology 60
  • Neurology 87
  • Pulmonary and Respiratory Medicine 106
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Cuiting Luo relative to Lianzi Wang China Lianzi Wang's profile →
Citations per field
00.5×3.5×
Lianzi Wang · 1×
Citations per year

Countries citing papers authored by Cuiting Luo

Since Specialization
Citations

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

Fields of papers citing papers by Cuiting Luo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

18 of 18 papers shown
#Work
1
Surgical Mask Partition Reduces the Risk of Noncontact Transmission in a Golden Syrian Hamster Model for Coronavirus Disease 2019 (COVID-19)
Hit paper breakdown →
2020400
2 202244
3 202139
4 202229
5 202313
6 20239
7 20248
8 20237
9 20225
10 20235
11 20224
12 20233
13 20233
14 20243
15 20231
16 20241
17 20231
18 20190

About Cuiting Luo

Cuiting Luo is a scholar working on Infectious Diseases, Molecular Biology, Oncology, Epidemiology and Artificial Intelligence, having authored 18 papers that have together received 575 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (6 papers), COVID-19 Clinical Research Studies (3 papers), Infection Control and Ventilation (2 papers), Adipose Tissue and Metabolism (2 papers), Trace Elements in Health (2 papers), Time Series Analysis and Forecasting (2 papers), vaccines and immunoinformatics approaches (2 papers) and Respiratory viral infections research (2 papers). The work is most often cited by research in Infectious Diseases (365 citations), Modeling and Simulation (70 citations), Animal Science and Zoology (60 citations), Neurology (87 citations) and Pulmonary and Respiratory Medicine (106 citations). Cuiting Luo has collaborated with scholars based in China, Hong Kong and Taiwan. Frequent co-authors include Shuofeng Yuan, Hin Chu, Kwok‐Yung Yuen, Jasper Fuk‐Woo Chan, Jian‐Piao Cai, Kaiming Tang, Kelvin Kai‐Wang To, Jianli Cao, Ronghui Liang and Vincent Kwok‐Man Poon. Their work appears in journals such as Clinical Infectious Diseases, Cellular and Molecular Immunology, Nature Communications, Frontiers in Immunology and Journal of Advanced Research.

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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