In‐Gu Jun

1.4k citations
82 papers · 995 indexed · h-index 18

Impact in

Papers in

    • Organ Transplantation Techniques and Outcomes 29
    • Hemodynamic Monitoring and Therapy 9
    • Liver Disease and Transplantation 29

In‐Gu Jun

75 papers receiving 985 citations

Peers

In‐Gu Jun
Comparison fields: 5 of 85
  • Hepatology 297
  • Critical Care and Intensive Care Medicine 125
  • Anesthesiology and Pain Medicine 87
  • Developmental Neuroscience 47
  • Nephrology 78
Replace Matthias Behrends with:
Matthias Behrends United States
Marleen Verhaegen Belgium
Aurora M. Morariu Netherlands
Ellen Ejlersen Denmark
Ryo Orii Japan
P. L. Goldiner United States
Yasuhide Iwao Japan
Dirk Scheinichen Germany
J Dall'Ava-Santucci France
Young Chul Yoo South Korea
In‐Gu Jun relative to Matthias Behrends United States Matthias Behrends's profile →
Citations per field
00.5×
Matthias Behrends · 1×
Citations per year

Countries citing papers authored by In‐Gu Jun

Since Specialization
Citations

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

Fields of papers citing papers by In‐Gu Jun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 82 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011166
2 201373
3 201356
4 200948
5 201940
6 201129
7 200928
8 201928
9 201924
10 201023
11 201921
12 201921
13 201619
14 201019
15 201719
16 201318
17 201218
18 202117
19 202116
20 201115

About In‐Gu Jun

In‐Gu Jun is a scholar working on Surgery, Hepatology, Cardiology and Cardiovascular Medicine, Physiology and Pulmonary and Respiratory Medicine, having authored 82 papers that have together received 995 indexed citations. Recurring topics across this work include Organ Transplantation Techniques and Outcomes (29 papers), Liver Disease and Transplantation (29 papers), Pain Mechanisms and Treatments (10 papers), Hemodynamic Monitoring and Therapy (9 papers), Liver Disease Diagnosis and Treatment (9 papers), Cardiac, Anesthesia and Surgical Outcomes (8 papers), Acute Kidney Injury Research (7 papers) and Botulinum Toxin and Related Neurological Disorders (6 papers). The work is most often cited by research in Hepatology (297 citations), Critical Care and Intensive Care Medicine (125 citations), Anesthesiology and Pain Medicine (87 citations), Developmental Neuroscience (47 citations) and Nephrology (78 citations). In‐Gu Jun has collaborated with scholars based in South Korea, United States and Canada. Frequent co-authors include Jun‐Gol Song, Gyu‐Sam Hwang, Young‐Jin Moon, Jong Yeon Park, Gyu Jeong Noh, UnCheol Lee, George A. Mashour, Won‐Jung Shin, Hye‐Mee Kwon and Young‐Kug Kim. Their work appears in journals such as Korean journal of anesthesiology, Journal of Korean Medical Science, Medicine, Anesthesia & Analgesia and Scientific Reports.

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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