Jun-Su Jang

536 citations
41 papers · 418 · h-index 11

Impact in

Papers in

Jun-Su Jang

38 papers receiving 378 citations

Peers

Jun-Su Jang
Comparison fields: 5 of 90
  • Complementary and alternative medicine 130
  • Computer Vision and Pattern Recognition 97
  • Artificial Intelligence 81
  • Health Information Management 8
  • Pharmacology 26
Replace Fufeng Li with:
Fufeng Li China
Tayo Obafemi-Ajayi United States
Zhengchen Zhang China
Donna L. Hudson United States
Mohammadreza Amirian Germany
Kun-chan Lan Taiwan
Tsung-Chieh Lee Taiwan
Kyeong-Seop Kim South Korea
Bart Bakker Netherlands
Jiang Pin China
Jun-Su Jang relative to Fufeng Li China Fufeng Li's profile →
Citations per field
00.5×1.5×2.4×
Fufeng Li · 1×
Citations per year

Countries citing papers authored by Jun-Su Jang

Since Specialization
Citations

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

Fields of papers citing papers by Jun-Su Jang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jun-Su Jang. 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-Su Jang. The network helps show where Jun-Su Jang may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201275
2 200837
3 200537
4 200332
5 200830
6 201328
7 202320
8 201315
9 200415
10 201312
11 201311
12 201210
13 201210
14 20137
15 20137
16 20226
17 20136
18 20066
19 20226
20 20175

About Jun-Su Jang

Jun-Su Jang is a scholar working on Biomedical Engineering, Complementary and alternative medicine, Computer Vision and Pattern Recognition, Pathology and Forensic Medicine and Artificial Intelligence, having authored 41 papers that have together received 418 indexed citations. Recurring topics across this work include Traditional Chinese Medicine Studies (13 papers), Medical Imaging and Analysis (11 papers), Spine and Intervertebral Disc Pathology (8 papers), Face and Expression Recognition (7 papers), Face recognition and analysis (6 papers), Acupuncture Treatment Research Studies (3 papers), Metaheuristic Optimization Algorithms Research (3 papers) and Membrane Separation Technologies (2 papers). The work is most often cited by research in Complementary and alternative medicine (130 citations), Computer Vision and Pattern Recognition (97 citations), Artificial Intelligence (81 citations), Health Information Management (8 citations) and Pharmacology (26 citations). Jun-Su Jang has collaborated with scholars based in South Korea, Thailand and United States. Frequent co-authors include Jong-Hwan Kim, Jong Yeol Kim, Boncho Ku, Kuk-Hyun Han, Jun‐Hyeong Do, Takeo Kanade, Eun-Su Jang, Keun Ho Kim, Bum Ju Lee and Young‐Su Kim. Their work appears in journals such as Evidence-based Complementary and Alternative Medicine, BMC Complementary and Alternative Medicine, Artificial Intelligence in Medicine, Medicine and Sensors.

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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