Ji Eun Jun

2.4k citations
71 papers · 1.7k · h-index 22

Impact in

Papers in

Ji Eun Jun

67 papers receiving 1.7k citations

Peers

Ji Eun Jun
Comparison fields: 5 of 113
  • Endocrinology, Diabetes and Metabolism 372
  • Physiology 244
  • Epidemiology 240
  • Cardiology and Cardiovascular Medicine 133
  • Nephrology 40
Replace Xiang Liu with:
Xiang Liu China
A. A. Driedger Canada
Yingying Hu China
Chenxi Song China
Chunguang Chen China
Jianhua Wang China
Arnon Blum Israel
Kazuya Murata Japan
Ke Deng China
Kuk Hui Son South Korea
Ji Eun Jun relative to Xiang Liu China Xiang Liu's profile →
Citations per field
00.5×6.3×
Xiang Liu · 1×
Citations per year

Countries citing papers authored by Ji Eun Jun

Since Specialization
Citations

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

Fields of papers citing papers by Ji Eun Jun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ji Eun 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 Ji Eun Jun. The network helps show where Ji Eun Jun may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 71 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004388
2 2018146
3 1996128
4 201998
5 201589
6 201867
7 201657
8 201844
9 202343
10 200640
11 201736
12 201835
13 201732
14 202131
15 202027
16 201826
17 201826
18 202125
19 201925
20 202222

About Ji Eun Jun

Ji Eun Jun is a scholar working on Endocrinology, Diabetes and Metabolism, Cardiology and Cardiovascular Medicine, Surgery, Molecular Biology and Physiology, having authored 71 papers that have together received 1.7k indexed citations. Recurring topics across this work include Heart Rate Variability and Autonomic Control (7 papers), Lipoproteins and Cardiovascular Health (7 papers), Diabetes Management and Research (6 papers), Nutrition and Health in Aging (5 papers), Diabetes Treatment and Management (5 papers), Thyroid Disorders and Treatments (5 papers), Gout, Hyperuricemia, Uric Acid (2 papers) and Metabolism, Diabetes, and Cancer (2 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (372 citations), Physiology (244 citations), Epidemiology (240 citations), Cardiology and Cardiovascular Medicine (133 citations) and Nephrology (40 citations). Ji Eun Jun has collaborated with scholars based in South Korea, Japan and United States. Frequent co-authors include Jae Hyeon Kim, Sang‐Man Jin, Kyu Yeon Hur, You‐Bin Lee, Ho Bum Park, Ji Won Rhim, Young Moo Lee, C LEE, Dong‐Hyun Kim and Moon‐Kyu Lee. Their work appears in journals such as Diabetes & Metabolism Journal, Cardiovascular Diabetology, Diabetes Research and Clinical Practice, Scientific Reports and Diabetes/Metabolism Research and Reviews.

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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