Jun‐Ma Yu

750 citations
32 papers · 505 · h-index 13

Impact in

Papers in

Jun‐Ma Yu

30 papers receiving 496 citations

Peers

Jun‐Ma Yu
Comparison fields: 5 of 59
  • Anesthesiology and Pain Medicine 78
  • Developmental Neuroscience 27
  • Obstetrics and Gynecology 44
  • Critical Care and Intensive Care Medicine 22
  • Endocrinology, Diabetes and Metabolism 66
Replace G. Shorten with:
G. Shorten Ireland
Yasuyuki Tokinaga Japan
Alese Wagner Canada
Yuji Takauchi Japan
Fatemeh Javaherforooshzadeh Iran
Mine Çelik Türkiye
R. K. Krothapalli United States
J. Sprung United States
Timothy M. Fernandes United States
Ichiro Takenaka Japan
Jun‐Ma Yu relative to G. Shorten Ireland G. Shorten's profile →
Citations per field
00.5×10×15×19.7×
G. Shorten · 1×
Citations per year

Countries citing papers authored by Jun‐Ma Yu

Since Specialization
Citations

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

Fields of papers citing papers by Jun‐Ma Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006130
2 201053
3 201741
4 201032
5 202219
6 201118
7 201218
8 201617
9 201916
10 201815
11 202313
12 202012
13 201612
14 201111
15 202210
16 202310
17 201210
18 19899
19 20228
20 20148

About Jun‐Ma Yu

Jun‐Ma Yu is a scholar working on Surgery, Anesthesiology and Pain Medicine, Pathology and Forensic Medicine, Physiology and Cardiology and Cardiovascular Medicine, having authored 32 papers that have together received 505 indexed citations. Recurring topics across this work include Anesthesia and Pain Management (8 papers), Anesthesia and Sedative Agents (5 papers), Cardiac Ischemia and Reperfusion (5 papers), Nausea and vomiting management (3 papers), Airway Management and Intubation Techniques (3 papers), Anesthesia and Neurotoxicity Research (3 papers), Cardiac, Anesthesia and Surgical Outcomes (2 papers) and Intensive Care Unit Cognitive Disorders (2 papers). The work is most often cited by research in Anesthesiology and Pain Medicine (78 citations), Developmental Neuroscience (27 citations), Obstetrics and Gynecology (44 citations), Critical Care and Intensive Care Medicine (22 citations) and Endocrinology, Diabetes and Metabolism (66 citations). Jun‐Ma Yu has collaborated with scholars based in China, Hong Kong and Germany. Frequent co-authors include Daiyu Hu, Yao Lu, Yanming Wu, Tao Duan, Peng Sun, Lining Wu, Qiang Lü, Chao Wu, Jun Zhang and Ye Zhang. Their work appears in journals such as Journal of Pain Research, BMC Anesthesiology, Medicine, Diabetic Medicine and Trials.

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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