Kaijiang Yu

108 papers receiving 2.1k citations

Kaijiang Yu's Hit Papers

The Epidemiology of Sepsis in Chinese ICUs: A National Cross-Sectional Survey 2019 · 311 citations
3110+2+4Years since publication100200300

Peers

Kaijiang Yu
Comparison fields: 5 of 127
  • Critical Care and Intensive Care Medicine 175
  • Epidemiology 369
  • Nephrology 78
  • Immunology 221
  • Cancer Research 149
Replace Stefan Hofer with:
Stefan Hofer Germany
Αναστασία Κοτανίδου Greece
Shinji Ogura Japan
Margaret J. Neff United States
Olivier Huet France
Giacomo Bellani Italy
María M. Martín Spain
George M. Matuschak United States
Raphaël Favory France
Anne M. Drewry United States
Kaijiang Yu relative to Stefan Hofer Germany Stefan Hofer's profile →
Citations per field
00.5×2×3×4×
Stefan Hofer · 1×
Citations per year

Countries citing papers authored by Kaijiang Yu

Since Specialization
Citations

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

Fields of papers citing papers by Kaijiang Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 112 papers — load more, or switch the sort, to bring in the rest.

#Work
1
The Epidemiology of Sepsis in Chinese ICUs: A National Cross-Sectional Survey
Hit paper breakdown →
2019311
2 2017131
3 2016119
4 2017105
5 201689
6 201679
7 201666
8 201964
9 202163
10
Dexmedetomidine alleviates LPS-induced septic cardiomyopathy via the cholinergic anti-inflammatory pathway in mice.
201756
11 201853
12 201844
13 202133
14 201833
15 202131
16 202228
17 201927
18 202127
19 201826
20 201626

About Kaijiang Yu

Kaijiang Yu is a scholar working on Molecular Biology, Infectious Diseases, Epidemiology, Neurology and Pulmonary and Respiratory Medicine, having authored 112 papers that have together received 2.1k indexed citations. Recurring topics across this work include Sepsis Diagnosis and Treatment (9 papers), COVID-19 Clinical Research Studies (9 papers), Acute Kidney Injury Research (8 papers), SARS-CoV-2 and COVID-19 Research (8 papers), Long-Term Effects of COVID-19 (8 papers), Gut microbiota and health (7 papers), Respiratory Support and Mechanisms (6 papers) and Intensive Care Unit Cognitive Disorders (6 papers). The work is most often cited by research in Critical Care and Intensive Care Medicine (175 citations), Epidemiology (369 citations), Nephrology (78 citations), Immunology (221 citations) and Cancer Research (149 citations). Kaijiang Yu has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Changsong Wang, Ruitao Wang, Hongliang Wang, Kai Kang, Yi Yang, Haitao Liu, Mingyan Zhao, Haibo Qiu, Jianfeng Xie and Yan Kang. Their work appears in journals such as Critical Care, The Journal of Infectious Diseases, Journal of Inflammation Research, International Immunopharmacology and Frontiers in Cellular and Infection Microbiology.

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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