Ye Shen

3.5k citations
109 papers · 1.9k · h-index 24

Impact in

Papers in

    • Influenza Virus Research Studies 17
    • Respiratory viral infections research 5
    • Tuberculosis Research and Epidemiology 7
    • COVID-19 Clinical Research Studies 5

Ye Shen

99 papers receiving 1.9k citations

Peers

Ye Shen
Comparison fields: 5 of 146
  • Infectious Diseases 286
  • Modeling and Simulation 73
  • Emergency Medicine 94
  • Epidemiology 305
  • Parasitology 58
Replace Julia L. Finkelstein with:
Julia L. Finkelstein United States
Anil Kumar Tripathi India
Gianluca Quaglio Italy
Kamija S. Phiri Malawi
Jane R. Zucker United States
André Karch Germany
Hao Liang China
Marcelo Ribeiro‐Alves Brazil
Andrew J. Hall United Kingdom
Ricardo Queiroz Gurgel Brazil
Ye Shen relative to Julia L. Finkelstein United States Julia L. Finkelstein's profile →
Citations per field
00.5×1.5×1.9×
Julia L. Finkelstein · 1×
Citations per year

Countries citing papers authored by Ye Shen

Since Specialization
Citations

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

Fields of papers citing papers by Ye Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 109 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013128
2 2020110
3 2017108
4 2005103
5 200694
6 201169
7 201863
8 200460
9 201958
10 202054
11 202151
12 202049
13 201948
14 201435
15 201235
16 201534
17 201334
18 201534
19 202333
20 201628

About Ye Shen

Ye Shen is a scholar working on Epidemiology, Infectious Diseases, Pediatrics, Perinatology and Child Health, Nutrition and Dietetics and Public Health, Environmental and Occupational Health, having authored 109 papers that have together received 1.9k indexed citations. Recurring topics across this work include Influenza Virus Research Studies (17 papers), Tuberculosis Research and Epidemiology (7 papers), Fatty Acid Research and Health (6 papers), Parasites and Host Interactions (6 papers), COVID-19 epidemiological studies (6 papers), Respiratory viral infections research (5 papers), COVID-19 Clinical Research Studies (5 papers) and Animal Disease Management and Epidemiology (5 papers). The work is most often cited by research in Infectious Diseases (286 citations), Modeling and Simulation (73 citations), Emergency Medicine (94 citations), Epidemiology (305 citations) and Parasitology (58 citations). Ye Shen has collaborated with scholars based in United States, China and Switzerland. Frequent co-authors include Changwei Li, Mark H. Ebell, Leonardo Martínez, Liu B, Luqi Shen, Woncheol Jang, Romergryko G. Geocadin, Toni P. Miles, Christopher C. Whalen and Zhenying Dong. Their work appears in journals such as The Journal of Infectious Diseases, American Journal of Tropical Medicine and Hygiene, PLoS ONE, Epidemiology and Infection and The Journal of the American Board of Family Medicine.

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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