Yuan Lv

724 citations
18 papers · 306 indexed · h-index 7
Topics
Diabetes Management and Research (3 papers)Neonatal and fetal brain pathology (2 papers)Antibiotic Resistance in Bacteria (2 papers)

In The Last Decade

Yuan Lv

17 papers receiving 301 citations

Peers

Yuan Lv
Comparison fields: 5 of 76
  • Infectious Diseases 151
  • Clinical Biochemistry 81
  • Molecular Biology 79
  • Molecular Medicine 78
  • Epidemiology 46
Replace Loubna Alavoine with:
Loubna Alavoine France
Lucia Mališová Czechia
Soma Sarkar India
Martha J. Gentry‐Nielsen United States
Elizabeth A. Lakota United States
Nathalie Mugnier France
Jeffrey Eckert United States
Satoshi Shimura Japan
Congrong Li China
Dong Hoon Shin South Korea
Yuan Lv relative to Loubna Alavoine France Loubna Alavoine's profile →
Citations per field
00.5×3.5×
Loubna Alavoine · 1×
Citations per year

Countries citing papers authored by Yuan Lv

Since Specialization
Citations

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

Fields of papers citing papers by Yuan Lv

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yuan Lv

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

All Works

18 of 18 papers shown
#WorkIndexed citations
1 2
2 1
3 3
4 3
5 3
6 5
7 6
8 4
9 11
10 7
11 5
12 32
13 120
14 55
15 17
16
Ministry of Health National Antimicrobial Resistance Investigation Net annual report of 2011: bacterial distribution and resistance in urinary tract infections in male
2
17 30
18
Investigation on correlation risk factors among longevity elderly with cardiovascular or cerebrovascular events
0

About Yuan Lv

Yuan Lv is a scholar working on Molecular Medicine, Endocrinology, Diabetes and Metabolism and Internal Medicine, having authored 18 papers that have together received 306 indexed citations. Recurring topics across this work include Diabetes Management and Research (3 papers), Neonatal and fetal brain pathology (2 papers) and Antibiotic Resistance in Bacteria (2 papers). The work is most often cited by research in Molecular Medicine (78 citations), Clinical Biochemistry (81 citations) and Infectious Diseases (151 citations). Yuan Lv has collaborated with scholars based in China, United States and Netherlands. Frequent co-authors include Yang Wang, Jiachang Cai, Tao He, Congming Wu, Štefan Schwarz, Yingbo Shen, Jun Li, Jianzhong Shen, Andrea T. Feßler and Rong Zhang. Their work appears in journals such as PLoS ONE, Antimicrobial Agents and Chemotherapy and Journal of Antimicrobial Chemotherapy.

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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