Ji Hee Jun

1k citations
70 papers · 767 · h-index 17

Impact in

Papers in

Ji Hee Jun

70 papers receiving 732 citations

Peers

Ji Hee Jun
Comparison fields: 5 of 80
  • Complementary and alternative medicine 336
  • Statistics, Probability and Uncertainty 42
  • Pharmacology 74
  • Urology 26
  • Complementary and Manual Therapy 7
Replace Yen‐Ying Kung with:
Yen‐Ying Kung Taiwan
Xiyan Zhao China
Xinyu Shi China
Jing Luo China
Marcus Reif Germany
Nam-Kwen Kim South Korea
Ciaran M. Fairman United States
Konstanze Diefenbach Germany
Bernard J. Lavins United States
Ji Hee Jun relative to Yen‐Ying Kung Taiwan Yen‐Ying Kung's profile →
Citations per field
00.5×5×10×13×
Yen‐Ying Kung · 1×
Citations per year

Countries citing papers authored by Ji Hee Jun

Since Specialization
Citations

This map shows the geographic impact of Ji Hee 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 Hee 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 Hee Jun more than expected).

Fields of papers citing papers by Ji Hee Jun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 70 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201468
2 201448
3 201545
4 202231
5 202130
6 202130
7 201529
8 201724
9 201422
10 201221
11 201421
12 201520
13 202020
14 201419
15 201718
16 201918
17 202218
18 201417
19 201915
20 201814

About Ji Hee Jun

Ji Hee Jun is a scholar working on Complementary and alternative medicine, Public Health, Environmental and Occupational Health, Endocrinology, Diabetes and Metabolism, Pharmacology and Statistics, Probability and Uncertainty, having authored 70 papers that have together received 767 indexed citations. Recurring topics across this work include Acupuncture Treatment Research Studies (24 papers), Traditional Chinese Medicine Studies (16 papers), Complementary and Alternative Medicine Studies (9 papers), Clinical practice guidelines implementation (8 papers), Medical Research and Treatments (8 papers), Menopause: Health Impacts and Treatments (5 papers), Medicinal Plant Extracts Effects (4 papers) and Meta-analysis and systematic reviews (3 papers). The work is most often cited by research in Complementary and alternative medicine (336 citations), Statistics, Probability and Uncertainty (42 citations), Pharmacology (74 citations), Urology (26 citations) and Complementary and Manual Therapy (7 citations). Ji Hee Jun has collaborated with scholars based in South Korea, China and Norway. Frequent co-authors include Myeong Soo Lee, Tae‐Young Choi, Jiae Choi, Ju Ah Lee, Lin Ang, Hye Won Lee, Hyun‐Ja Lim, Jong‐In Kim, Sooseong You and Ju Ah Lee. Their work appears in journals such as Medicine, BMJ Open, Maturitas, Journal of Clinical Medicine and Frontiers in Neurology.

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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