Sungmin Jun
Impact in
-
- Medical Imaging Techniques and Applications
- Radiomics and Machine Learning in Medical Imaging
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- Infectious Diseases and Tuberculosis
- Diagnosis and treatment of tuberculosis
Papers in
- Surgery 3
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- Lymphoma Diagnosis and Treatment 2
- Co-authors
- Seong‐Jang Kim (4 shared papers)In‐Ju Kim (5 shared papers)Jung Sub Lee (3 shared papers)Yeon Joo Jeong (1 shared paper)Hyun‐Yeol Nam (6 shared papers)Yong‐Ki Kim (1 shared paper)Heeyoung Kim (6 shared papers)Yong-Ki Kim (3 shared papers)
- Journals
- Journal of Alzheimer s Disease (3 papers)Skeletal Radiology (1 paper)Cell Proliferation (1 paper)Journal of Nuclear Medicine (1 paper)Journal of Computer Assisted Tomography (1 paper)
- Partner nations
- South KoreaNew Zealand
In The Last Decade
Sungmin Jun
25 papers receiving 313 citations
Peers
Comparison fields: 5 of 64
- Radiology, Nuclear Medicine and Imaging 53
- Surgery 95
- Infectious Diseases 40
- Endocrinology, Diabetes and Metabolism 28
- Genetics 17
Countries citing papers authored by Sungmin Jun
This map shows the geographic impact of Sungmin 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 Sungmin Jun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sungmin Jun more than expected).
Fields of papers citing papers by Sungmin Jun
This network shows the impact of papers produced by Sungmin 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 Sungmin Jun. The network helps show where Sungmin Jun may publish in the future.
Co-authors
The 25 scholars most cited alongside Sungmin Jun, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2007 | 84 | |
| 2 | 2008 | 30 | |
| 3 | 2007 | 27 | |
| 4 | 2009 | 26 | |
| 5 | 2019 | 21 | |
| 6 | 2016 | 21 | |
| 7 | 2017 | 18 | |
| 8 | 2017 | 11 | |
| 9 | 2021 | 9 | |
| 10 | 2017 | 9 | |
| 11 | 2021 | 8 | |
| 12 | 2016 | 8 | |
| 13 | 2019 | 8 | |
| 14 | 2023 | 6 | |
| 15 | 2018 | 6 | |
| 16 | 2019 | 5 | |
| 17 | 2017 | 5 | |
| 18 | 2023 | 4 | |
| 19 | 2015 | 4 | |
| 20 | 2020 | 4 |
About Sungmin Jun
Sungmin Jun is a scholar working on Surgery, Pathology and Forensic Medicine, Neurology, Rheumatology and Radiology, Nuclear Medicine and Imaging, having authored 27 papers that have together received 323 indexed citations. Recurring topics across this work include Lymphoma Diagnosis and Treatment (2 papers), Dementia and Cognitive Impairment Research (2 papers), MRI in cancer diagnosis (1 paper), Neurofibromatosis and Schwannoma Cases (1 paper), Neurosurgical Procedures and Complications (1 paper), Microfluidic and Bio-sensing Technologies (1 paper), Medical Imaging Techniques and Applications (1 paper) and Single-cell and spatial transcriptomics (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (53 citations), Surgery (95 citations), Infectious Diseases (40 citations), Endocrinology, Diabetes and Metabolism (28 citations) and Genetics (17 citations). Sungmin Jun has collaborated with scholars based in South Korea and New Zealand. Frequent co-authors include Seong‐Jang Kim, In‐Ju Kim, Jung Sub Lee, Yeon Joo Jeong, Hyun‐Yeol Nam, Yong‐Ki Kim, Heeyoung Kim, Yong-Ki Kim, In Sook Lee and Kyoungjune Pak. Their work appears in journals such as Journal of Alzheimer s Disease, Skeletal Radiology, Cell Proliferation, Journal of Nuclear Medicine and Journal of Computer Assisted Tomography.
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.