Kaihuan Yu

1.3k total citations · 1 hit paper
31 papers, 718 citations indexed

About

Kaihuan Yu is a scholar working on Molecular Biology, Infectious Diseases and Neurology. According to data from OpenAlex, Kaihuan Yu has authored 31 papers receiving a total of 718 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 10 papers in Infectious Diseases and 9 papers in Neurology. Recurrent topics in Kaihuan Yu's work include COVID-19 Clinical Research Studies (10 papers), Long-Term Effects of COVID-19 (9 papers) and SARS-CoV-2 and COVID-19 Research (4 papers). Kaihuan Yu is often cited by papers focused on COVID-19 Clinical Research Studies (10 papers), Long-Term Effects of COVID-19 (9 papers) and SARS-CoV-2 and COVID-19 Research (4 papers). Kaihuan Yu collaborates with scholars based in China, United States and Canada. Kaihuan Yu's co-authors include Zhe Luo, Zheyong Huang, Jiatian Cao, Yumeng Yao, Bijie Hu, Sisi Chen, Xiang Chen, Qingqing Wang, Qingfeng Shi and Kai Liu and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and World Journal of Gastroenterology.

In The Last Decade

Kaihuan Yu

29 papers receiving 702 citations

Hit Papers

D-dimer as a biomarker for disease severity and mortality... 2020 2026 2022 2024 2020 100 200 300 400

Peers

Kaihuan Yu
Comparison fields: 5 of 95
  • Infectious Diseases 453
  • Neurology 211
  • Oncology 156
  • Molecular Biology 113
  • Epidemiology 88
Replace Monia Maccaferri with:
Monia Maccaferri Italy
Tobias Weinberger Germany
Sichao Chen China
Nicola Boffini Italy
Pierre‐André Jarrot France
Panagiota Gianni Germany
Kai Dai China
Ding Long China
Wenhui Huang China
Monia Maccaferri Italy View profile →
Citations per field, relative to Kaihuan Yu
Kaihuan Yu · 1×
Citations per year, relative to Kaihuan Yu
Kaihuan Yu · 1×

Countries citing papers authored by Kaihuan Yu

Since Specialization
Citations

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

Fields of papers citing papers by Kaihuan Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kaihuan Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Kaihuan Yu. A scholar is included among the top collaborators of Kaihuan Yu 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 Kaihuan Yu. Kaihuan Yu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 4
2 3
3 0
4 6
5 1
6 5
7 0
8
Identification of Prognostic Genes in Hepatocellular Carcinoma
2
9 3
10 3
11 5
12 3
13 5
14 15
15 39
16 59
17 4
18 16
19 36
20 11

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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