Sung-Jong Eun

547 citations
49 papers · 377 · h-index 10

Impact in

    • Artificial Intelligence in Healthcare and Education
  • Urology top 10%
    • Urinary Bladder and Prostate Research

Papers in

Sung-Jong Eun

37 papers receiving 358 citations

Peers

Sung-Jong Eun
Comparison fields: 5 of 110
  • Health Informatics 22
  • Urology 45
  • Human-Computer Interaction 22
  • Psychiatry and Mental health 44
  • Health Information Management 13
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Ankita Singh India
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Shannon Rego United States
Matteo Pastorino Spain
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Francisco R. Ávila United States
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Citations per field
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Citations per year

Countries citing papers authored by Sung-Jong Eun

Since Specialization
Citations

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

Fields of papers citing papers by Sung-Jong Eun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sung-Jong Eun. 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 Sung-Jong Eun. The network helps show where Sung-Jong Eun may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201670
2 200847
3 202231
4 202230
5 201825
6 201317
7 202112
8 200511
9 202210
10 20189
11 20229
12 20179
13 20228
14 20228
15 20218
16 20178
17 20237
18 20196
19 20235
20 20234

About Sung-Jong Eun

Sung-Jong Eun is a scholar working on Computer Vision and Pattern Recognition, Pulmonary and Respiratory Medicine, Urology, Information Systems and Radiology, Nuclear Medicine and Imaging, having authored 49 papers that have together received 377 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (5 papers), Urinary Bladder and Prostate Research (5 papers), Kidney Stones and Urolithiasis Treatments (4 papers), Advanced MRI Techniques and Applications (4 papers), Education and Learning Interventions (4 papers), Brain Tumor Detection and Classification (3 papers), Medical Imaging Techniques and Applications (3 papers) and Image and Object Detection Techniques (3 papers). The work is most often cited by research in Health Informatics (22 citations), Urology (45 citations), Human-Computer Interaction (22 citations), Psychiatry and Mental health (44 citations) and Health Information Management (13 citations). Sung-Jong Eun has collaborated with scholars based in South Korea, United States and Japan. Frequent co-authors include Jungyoon Kim, Taeg Keun Whangbo, Eun Joung Kim, Khae Hawn Kim, Su Jin Kim, Dong Kyun Park, Seung Hyun Lee, Sung Tae Cho, Yong‐Ku Kim and Gwang‐Woo Jeong. Their work appears in journals such as Multimedia Tools and Applications, IEEE Access, International Neurourology Journal, Journal of Environmental and Public Health and PLoS ONE.

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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