Seong‐Jang Kim

6.2k total citations · 1 hit paper
228 papers, 4.5k citations indexed

About

Seong‐Jang Kim is a scholar working on Radiology, Nuclear Medicine and Imaging, Surgery and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Seong‐Jang Kim has authored 228 papers receiving a total of 4.5k indexed citations (citations by other indexed papers that have themselves been cited), including 88 papers in Radiology, Nuclear Medicine and Imaging, 65 papers in Surgery and 54 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Seong‐Jang Kim's work include Medical Imaging Techniques and Applications (48 papers), Radiomics and Machine Learning in Medical Imaging (47 papers) and Thyroid Cancer Diagnosis and Treatment (46 papers). Seong‐Jang Kim is often cited by papers focused on Medical Imaging Techniques and Applications (48 papers), Radiomics and Machine Learning in Medical Imaging (47 papers) and Thyroid Cancer Diagnosis and Treatment (46 papers). Seong‐Jang Kim collaborates with scholars based in South Korea, United States and Australia. Seong‐Jang Kim's co-authors include Kyoungjune Pak, Sung Ryul Shim, Jong Hoo Lee, In Joo Kim, In Joo Kim, Keunyoung Kim, Keunyoung Kim, Yong-Ki Kim, Sang‐Woo Lee and Gerta Rücker and has published in prestigious journals such as PLoS ONE, The Journal of Clinical Endocrinology & Metabolism and Scientific Reports.

In The Last Decade

Seong‐Jang Kim

225 papers receiving 4.4k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Network meta-analysis: application and practice using R software

2019 331 citations Sung Ryul Shim, Seong‐Jang Kim et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Seong‐Jang Kim South Korea	33	1.5k	1.3k	1.2k	808	740	228	4.5k
Brian P. Mullan United States	43	1.3k 0.8×	2.0k 1.5×	1.0k 0.9×	1.1k 1.4×	517 0.7×	121	6.6k
Yoshito Tsushima Japan	38	1.9k 1.2×	1.2k 0.9×	828 0.7×	412 0.5×	568 0.8×	338	5.4k
Masayuki Nakajo Japan	37	1.2k 0.8×	1.9k 1.4×	891 0.8×	605 0.7×	704 1.0×	217	4.5k
Marcel P. M. Stokkel Netherlands	44	3.0k 2.0×	1.9k 1.4×	828 0.7×	1.8k 2.2×	1.1k 1.4×	243	7.6k
D. Huglo France	29	868 0.6×	746 0.6×	801 0.7×	406 0.5×	561 0.8×	120	3.6k
Kei Takase Japan	39	1.2k 0.8×	1.8k 1.3×	1.3k 1.1×	837 1.0×	295 0.4×	241	4.0k
Martin Torriani United States	47	661 0.4×	2.2k 1.6×	813 0.7×	772 1.0×	412 0.6×	205	7.2k
Sang Joon Kim South Korea	42	2.0k 1.3×	1.4k 1.0×	1.4k 1.2×	349 0.4×	218 0.3×	288	6.1k
G. Brandon Gunn United States	45	1.1k 0.7×	1.9k 1.5×	2.8k 2.4×	997 1.2×	1.8k 2.4×	288	6.8k
K. Masuda Japan	35	1.0k 0.7×	1.1k 0.8×	951 0.8×	143 0.2×	498 0.7×	174	4.2k

Countries citing papers authored by Seong‐Jang Kim

Since Specialization

Citations

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

Fields of papers citing papers by Seong‐Jang Kim

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Seong‐Jang Kim. 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 Seong‐Jang Kim. The network helps show where Seong‐Jang Kim may publish in the future.

Co-authorship network of co-authors of Seong‐Jang Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Seong‐Jang Kim. A scholar is included among the top collaborators of Seong‐Jang Kim 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 Seong‐Jang Kim. Seong‐Jang Kim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Kim, Seong‐Jang, Taeho Greg Rhee, & Sung Ryul Shim. (2023). Autoimmune and auto-inflammatory adverse events after COVID-19 vaccination in the United States. Clinical Immunology. 259. 109882–109882. 2 indexed citations

Shim, Sung Ryul, Dayeon Shin, Seong‐Jang Kim, Young Kook Kim, & Kyung Ju Lee. (2023). Unveiling the Therapeutic Potential and Healthcare Applications of Marine Therapy: A Systematic Review with Meta-Analysis and Meta-Regression. Marine Drugs. 21(12). 604–604. 1 indexed citations

Kim, Seong‐Jang, et al.. (2023). Diagnostic performance of ¹⁸F-FDG PET or PET/CT for detection of myocarditis.. PubMed. 26(2). 132–139. 1 indexed citations

Lee, Sang‐Woo, Shin Young Jeong, Keunyoung Kim, & Seong‐Jang Kim. (2021). Direct comparison of F-18 FDG PET/CT and MRI to predict pathologic response to neoadjuvant treatment in locally advanced rectal cancer: a meta-analysis. Annals of Nuclear Medicine. 35(9). 1038–1047. 5 indexed citations

Kim, Sun Il, Se Joong Kim, Seong‐Jang Kim, & Dae Sung Cho. (2021). Prognostic nutritional index and prognosis in renal cell carcinoma: A systematic review and meta-analysis. Urologic Oncology Seminars and Original Investigations. 39(10). 623–630. 15 indexed citations

Pak, Kyoungjune, Mijin Kim, Keunyoung Kim, et al.. (2020). Cerebral glucose metabolism and Cerebral blood flow in thyroid dysfunction: An Activation Likelihood Estimation Meta-analysis. Scientific Reports. 10(1). 1335–1335. 6 indexed citations

Kim, Keunyoung & Seong‐Jang Kim. (2020). Diagnostic performance of F-18 fluorodeoxyglucose PET/computed tomography for diagnosis of polymyalgia rheumatica: a meta-analysis. Nuclear Medicine Communications. 41(12). 1313–1321. 4 indexed citations

Kim, Seong‐Jang, Sang‐Woo Lee, Shin Young Jeong, Kyoungjune Pak, & Keunyoung Kim. (2019). A systematic review and meta-analysis of 18F-fluorodeoxyglucose positron emission tomography or positron emission tomography/computed tomography for detection of infected prosthetic vascular grafts. Journal of Vascular Surgery. 70(1). 307–313. 20 indexed citations

Kim, Seong‐Jang, Sang‐Woo Lee, & Hong Koo Ha. (2018). Diagnostic Performance of Radiolabeled Prostate-Specific Membrane Antigen Positron Emission Tomography/Computed Tomography for Primary Lymph Node Staging in Newly Diagnosed Intermediate to High-Risk Prostate Cancer Patients: A Systematic Review and Meta-Analysis. Urologia Internationalis. 102(1). 27–36. 41 indexed citations

10.

Suh, Sunghwan, Yun Hak Kim, Tae Sik Goh, et al.. (2018). mRNA Expression of SLC5A5 and SLC2A Family Genes in Papillary Thyroid Cancer: An Analysis of The Cancer Genome Atlas. Yonsei Medical Journal. 59(6). 746–746. 7 indexed citations

11.

Pak, Kyoungjune, Ju Won Seok, Eun‐Joo Kim, et al.. (2018). Effect of rs3910105 in the Synuclein Gene on Dopamine Transporter Availability in Healthy Subjects. Yonsei Medical Journal. 59(6). 787–787. 3 indexed citations

12.

Lee, Su In, Dae Kyoung Kim, Eun Jin Seo, et al.. (2017). Role of Krüppel-Like Factor 4 in the Maintenance of Chemoresistance of Anaplastic Thyroid Cancer. Thyroid. 27(11). 1424–1432. 22 indexed citations

13.

Chang, Samuel & Seong‐Jang Kim. (2016). Prediction of Recurrence and Mortality of Locally Advanced Esophageal Cancer Patients Using Pretreatment F-18 FDG PET/CT Parameters: Intratumoral Heterogeneity, SUV, and Volumetric Parameters. Cancer Biotherapy and Radiopharmaceuticals. 31(1). 1–6. 18 indexed citations

14.

Kim, Heeyoung, Myung‐Jun Shin, Seong‐Jang Kim, In Joo Kim, & Il‐Kyu Park. (2014). The Relation of Visualization of Internal Mammary Lymph Nodes on Lymphoscintigraphy to Axillary Lymph Node Metastases in Breast Cancer. Lymphatic Research and Biology. 12(4). 295–300. 7 indexed citations

15.

Lee, Geewon, I Hoseok, Seong‐Jang Kim, et al.. (2014). Clinical Implication of PET/MR Imaging in Preoperative Esophageal Cancer Staging: Comparison with PET/CT, Endoscopic Ultrasonography, and CT. Journal of Nuclear Medicine. 55(8). 1242–1247. 65 indexed citations

16.

Kim, Heeyoung, Seong‐Jang Kim, In Joo Kim, & Keunyoung Kim. (2013). Thyroid Incidentalomas on FDG PET/CT in Patients with Non-Thyroid Cancer - a Large Retrospective Monocentric Study. Oncology Research and Treatment. 36(5). 260–264. 21 indexed citations

17.

Pak, Kyoungjune, Seong‐Jang Kim, In Joo Kim, et al.. (2013). The role of 18F-fluorodeoxyglucose positron emission tomography in differentiated thyroid cancer before surgery. Endocrine Related Cancer. 20(4). R203–R213. 24 indexed citations

18.

Kim, Bum‐Soo, et al.. (2012). Factors Associated with Positive F-18 Flurodeoxyglucose Positron Emission Tomography Before Thyroidectomy in Patients with Papillary Thyroid Carcinoma. Thyroid. 22(7). 725–729. 20 indexed citations

19.

Lee, Jun S., et al.. (2007). Comparison of gated blood pool SPECT and spiral multidetector computed tomography in the assessment of right ventricular functional parameters: validation with first-pass radionuclide angiography. Annals of Nuclear Medicine. 21(3). 159–166. 5 indexed citations

20.

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

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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