Sungmin Jun

421 total citations
27 papers, 302 citations indexed

About

Sungmin Jun is a scholar working on Radiology, Nuclear Medicine and Imaging, Surgery and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Sungmin Jun has authored 27 papers receiving a total of 302 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Radiology, Nuclear Medicine and Imaging, 6 papers in Surgery and 5 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Sungmin Jun's work include Medical Imaging Techniques and Applications (6 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and MRI in cancer diagnosis (3 papers). Sungmin Jun is often cited by papers focused on Medical Imaging Techniques and Applications (6 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and MRI in cancer diagnosis (3 papers). Sungmin Jun collaborates with scholars based in South Korea and New Zealand. Sungmin Jun's co-authors include Seong‐Jang Kim, Jung Sub Lee, In‐Ju Kim, Hyun‐Yeol Nam, Yeon Joo Jeong, Yong‐Ki Kim, Heeyoung Kim, Yong-Ki Kim, In Sook Lee and Kyoungjune Pak and has published in prestigious journals such as Biotechnology and Bioengineering, Annals of Surgical Oncology and Journal of Nuclear Medicine.

In The Last Decade

Sungmin Jun

25 papers receiving 295 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Sungmin Jun South Korea 10 120 76 53 50 42 27 302
Hwa Seon Shin South Korea 12 84 0.7× 134 1.8× 43 0.8× 115 2.3× 51 1.2× 42 421
Narayan Lath Singapore 8 67 0.6× 59 0.8× 43 0.8× 25 0.5× 43 1.0× 16 347
Marco Dell’Aquila Italy 13 53 0.4× 39 0.5× 42 0.8× 39 0.8× 38 0.9× 27 275
Konstantinos A. A. Douglas United States 10 51 0.4× 71 0.9× 17 0.3× 49 1.0× 48 1.1× 38 351
Ivan Marjanović Serbia 11 70 0.6× 66 0.9× 13 0.2× 66 1.3× 24 0.6× 67 373
T. Baysal Türkiye 11 99 0.8× 53 0.7× 13 0.2× 77 1.5× 20 0.5× 22 320
Paul Beech Australia 10 74 0.6× 49 0.6× 26 0.5× 42 0.8× 64 1.5× 23 310
Takuro Horikoshi Japan 12 102 0.8× 173 2.3× 13 0.2× 100 2.0× 45 1.1× 53 440
Juveria Siddiqui United Kingdom 8 128 1.1× 29 0.4× 69 1.3× 33 0.7× 26 0.6× 15 351
Thomas C. Lee United States 11 90 0.8× 63 0.8× 12 0.2× 68 1.4× 35 0.8× 18 375

Countries citing papers authored by Sungmin Jun

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Sungmin Jun

This figure shows the co-authorship network connecting the top 25 collaborators of Sungmin Jun. A scholar is included among the top collaborators of Sungmin Jun 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 Sungmin Jun. Sungmin Jun 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
1.
Choi, Jin‐Hyuk, et al.. (2024). Clinical Outcomes in Patients With DLBCL Treated With R-CHOP According to Radiotherapy and Interim PET Response. Cancer Diagnosis & Prognosis. 4(2). 172–181. 1 indexed citations
2.
Lee, Hyoung Shin, et al.. (2023). Shaving Papillary Thyroid Carcinoma Involving Functioning Recurrent Laryngeal Nerve: Safety of Incomplete Tumor Resection and Nerve Sparing. Annals of Surgical Oncology. 30(12). 7157–7164. 6 indexed citations
3.
Jun, Sungmin, et al.. (2022). Impact of Off-Hour Admission with Subarachnoid Hemorrhage: A Meta-Analysis. World Neurosurgery. 166. e872–e891. 2 indexed citations
4.
Yu, Jane, et al.. (2021). Can ECIS Biosensor Technology Be Used to Measure the Cellular Responses of Glioblastoma Stem Cells?. Biosensors. 11(12). 498–498. 9 indexed citations
5.
Jun, Sungmin, et al.. (2021). Effect of white matter hyperintensity on dopamine transporter availability of striatum measured by F-18 FP-CIT PET. Japanese Journal of Radiology. 39(11). 1097–1102. 2 indexed citations
6.
Jun, Sungmin, et al.. (2020). Differentiation of bone metastases from prostate cancer and benign red marrow depositions of the pelvic bone with multiparametric MRI. Magnetic Resonance Imaging. 73. 118–124. 3 indexed citations
7.
Jun, Sungmin, et al.. (2019). Quantitative Brain Amyloid Measures Predict Time-to-Progression from Amnestic Mild Cognitive Impairment to Alzheimer’s Disease. Journal of Alzheimer s Disease. 70(2). 477–486. 8 indexed citations
8.
9.
Pak, Kyoungjune, Bum Soo Kim, Keunyoung Kim, et al.. (2017). Prognostic significance of standardized uptake value on F18-FDG PET/CT in patients with extranodal nasal type NK/T cell lymphoma: A multicenter, retrospective analysis. American Journal of Otolaryngology. 39(1). 1–5. 17 indexed citations
10.
Nam, Hyun‐Yeol & Sungmin Jun. (2017). Association between active brown adipose tissue and coronary artery calcification in healthy men. Nuklearmedizin - NuclearMedicine. 56(5). 184–190. 11 indexed citations
11.
12.
Nam, Hyun‐Yeol, Sungmin Jun, Kyoungjune Pak, & In Joo Kim. (2017). Concurrent Low Brain and High Liver Uptake on FDG PET Are Associated with Cardiovascular Risk Factors. Korean Journal of Radiology. 18(2). 392–392. 9 indexed citations
13.
Kim, Heeyoung, et al.. (2016). Intravertebral vacuum cleft sign: a cause of vertebral cold defect on bone scan. Skeletal Radiology. 45(5). 707–712. 7 indexed citations
14.
Seo, Minjung, et al.. (2016). Follow-up bone scan in breast cancer patients. Nuclear Medicine Communications. 37(12). 1318–1324.
15.
Jun, Sungmin, Jong Jin Lee, Tae Yong Kim, et al.. (2015). Prediction of treatment response to 131I therapy by diffuse hepatic uptake intensity on post-therapy whole-body scan in patients with distant metastases of differentiated thyroid cancer. Annals of Nuclear Medicine. 29(7). 603–612. 4 indexed citations
16.
Jun, Sungmin, et al.. (2009). Camparison between the 1 Day and the 2 Day Protocols of Lymphoscintigraphy and Sentinel Node Biopsy using Subareolar Injection in Breast Cancer Patients: A Retrospective Study. Nuclear Medicine and Molecular Imaging. 43(1). 55–59. 1 indexed citations
17.
Lee, In Sook, et al.. (2009). Fluorine-18-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography Imaging in Pyogenic and Tuberculous Spondylitis. Journal of Computer Assisted Tomography. 33(4). 587–592. 26 indexed citations
18.
Jun, Sungmin, Yong-Ki Kim, In‐Ju Kim, Hyun‐Yeol Nam, & Bum Soo Kim. (2008). Innumerable Small Bony Nodular Sclerotic Lesions with Negative Findings on Both Bone Scintigraphy and F-18 FDG PET : Osteopoikilosis in a Patient of Breast Cancer. Nuclear Medicine and Molecular Imaging. 42(3). 256–258.
19.
Kim, Seong‐Jang, In‐Ju Kim, Yong-Ki Kim, et al.. (2007). Probabilistic Anatomic Mapping of Cerebral Blood Flow Distribution of the Middle Cerebral Artery. Journal of Nuclear Medicine. 49(1). 39–43. 24 indexed citations
20.
Kim, In‐Ju, Jung Sub Lee, Seong‐Jang Kim, et al.. (2007). Double-phase 18F-FDG PET-CT for determination of pulmonary tuberculoma activity. European Journal of Nuclear Medicine and Molecular Imaging. 35(4). 808–814. 78 indexed citations

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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