Seunggyun Ha

2.4k citations
82 papers · 1.7k indexed · h-index 20
Topics
Radiomics and Machine Learning in Medical Imaging (19 papers)Medical Imaging Techniques and Applications (13 papers)Parkinson's Disease Mechanisms and Treatments (13 papers)

In The Last Decade

Seunggyun Ha

77 papers receiving 1.6k citations

Peers

Seunggyun Ha
Comparison fields: 5 of 137
  • Radiology, Nuclear Medicine and Imaging 610
  • Molecular Biology 278
  • Pulmonary and Respiratory Medicine 252
  • Biomedical Engineering 219
  • Management Science and Operations Research 201
Replace Bing Jiang with:
Bing Jiang China
Chung‐Ho Chen Taiwan
Hao Yang China
Qin Yu China
Zeynep H. Gümüş United States
Aaron Weiss United States
Weilong Liu China
Hiroshi Maruyama Japan
Chun Zhao China
Nilamadhab Mishra India
Seunggyun Ha relative to Bing Jiang China Bing Jiang's profile →
Citations per field
00.5×7.3×
Bing Jiang · 1×
Citations per year

Countries citing papers authored by Seunggyun Ha

Since Specialization
Citations

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

Fields of papers citing papers by Seunggyun Ha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Seunggyun Ha. 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 Seunggyun Ha. The network helps show where Seunggyun Ha may publish in the future.

Co-authorship network of co-authors of Seunggyun Ha

This figure shows the co-authorship network connecting the top 25 collaborators of Seunggyun Ha. A scholar is included among the top collaborators of Seunggyun Ha based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Seunggyun Ha. Seunggyun Ha is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 1
3 3
4 1
5 1
6 3
7 1
8 2
9 5
10 7
11 29
12 1
13 46
14 99
15 122
16 21
17 42
18
PMMA Retinal Tack with Barb-shaped Scale bars for Retinal Prosthesis
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19 5
20 23

About Seunggyun Ha

Seunggyun Ha is a scholar working on Radiology, Nuclear Medicine and Imaging, Neurology and Animal Science and Zoology, having authored 82 papers that have together received 1.7k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (19 papers), Medical Imaging Techniques and Applications (13 papers) and Parkinson's Disease Mechanisms and Treatments (13 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (610 citations), Management Science and Operations Research (201 citations) and Management Information Systems (135 citations). Seunggyun Ha has collaborated with scholars based in South Korea, United States and Ethiopia. Frequent co-authors include Ramesh Krishnan, Hongyoon Choi, Dong Soo Lee, Gi Jeong Cheon, Steven C. Ricke, Jin Chul Paeng, Ho‐Young Lee, Sun Ha Paek, Hyung Jun Im and Dong Soo Lee. Their work appears in journals such as PLoS ONE, Bioresource Technology 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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