Jae Seok Kim

998 total citations
43 papers, 545 citations indexed

About

Jae Seok Kim is a scholar working on Nephrology, Cardiology and Cardiovascular Medicine and Physiology. According to data from OpenAlex, Jae Seok Kim has authored 43 papers receiving a total of 545 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Nephrology, 10 papers in Cardiology and Cardiovascular Medicine and 7 papers in Physiology. Recurrent topics in Jae Seok Kim's work include Dialysis and Renal Disease Management (8 papers), Body Composition Measurement Techniques (7 papers) and Cardiovascular Function and Risk Factors (6 papers). Jae Seok Kim is often cited by papers focused on Dialysis and Renal Disease Management (8 papers), Body Composition Measurement Techniques (7 papers) and Cardiovascular Function and Risk Factors (6 papers). Jae Seok Kim collaborates with scholars based in South Korea, Austria and United States. Jae Seok Kim's co-authors include Byoung Geun Han, Jae Won Yang, Jun Young Lee, Seung Ok Choi, Jang‐Young Kim, Ji Hye Huh, Eun Hee Choi, Ki‐Chul Sung, Min-Keun Kim and Jae Won Yang and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Jae Seok Kim

39 papers receiving 534 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jae Seok Kim South Korea 14 182 120 105 100 97 43 545
Maryna Masyuk Germany 15 103 0.6× 139 1.2× 256 2.4× 71 0.7× 35 0.4× 40 748
Kağan Huysal Türkiye 11 61 0.3× 120 1.0× 110 1.0× 79 0.8× 22 0.2× 35 577
Jou‐Wei Lin Taiwan 15 43 0.2× 213 1.8× 103 1.0× 41 0.4× 56 0.6× 27 584
Roberta Domizi Italy 17 68 0.4× 111 0.9× 338 3.2× 45 0.5× 54 0.6× 31 732
Ibrahim M. Saeed United States 14 41 0.2× 222 1.9× 52 0.5× 105 1.1× 59 0.6× 42 539
Young Ki Lee South Korea 12 168 0.9× 18 0.1× 42 0.4× 218 2.2× 154 1.6× 39 612
F. Meisner Germany 15 43 0.2× 102 0.8× 130 1.2× 49 0.5× 27 0.3× 29 538
Michael Lichtenauer Austria 15 35 0.2× 351 2.9× 133 1.3× 134 1.3× 44 0.5× 92 721
Ádám L. Jermendy Hungary 12 25 0.1× 278 2.3× 96 0.9× 68 0.7× 59 0.6× 42 544

Countries citing papers authored by Jae Seok Kim

Since Specialization
Citations

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

Fields of papers citing papers by Jae Seok Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jae Seok 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 Jae Seok Kim. The network helps show where Jae Seok Kim may publish in the future.

Co-authorship network of co-authors of Jae Seok Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Jae Seok Kim. A scholar is included among the top collaborators of Jae Seok 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 Jae Seok Kim. Jae Seok Kim 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.
Kim, Deok Gie, Sung Hwa Kim, Sung Yong Park, et al.. (2024). Anticoagulation in patients with end-stage kidney disease and atrial fibrillation: a national population-based study. Clinical Kidney Journal. 17(2). sfae029–sfae029. 4 indexed citations
2.
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Lee, Jun Young, et al.. (2023). #4666 ASSOCIATION BETWEEN URINARY ALBUMIN CREATININE RATIO AND CARDIOVASCULAR DISEASE. Nephrology Dialysis Transplantation. 38(Supplement_1). 2 indexed citations
5.
Lee, Jun Young, et al.. (2022). Pathological validation of the Japanese Renal Pathology Society classification and challenges in predicting renalprognosis in patients with diabetic nephropathy. Kidney Research and Clinical Practice. 41(5). 545–555. 3 indexed citations
6.
Kim, Deok Gie, Sung Hwa Kim, Jae Seok Kim, et al.. (2021). Survival Benefit of Anticoagulation Therapy in End Stage Kidney Disease Patients with Atrial Fibrillation: A Single Center Retrospective Study. Medicina. 58(1). 58–58. 9 indexed citations
7.
Han, Byoung Geun, Jun Young Lee, Jae Seok Kim, et al.. (2020). Fluid overload is a determinant for cardiac structural and functional impairments in type 2 diabetes mellitus and chronic kidney disease stage 5 not undergoing dialysis. PLoS ONE. 15(7). e0235640–e0235640. 13 indexed citations
8.
Lee, Jun Young, Seung Ok Choi, You Jin Kim, et al.. (2020). P0790RISK OF CARDIOVASCULAR DISEASE AND CHRONIC KIDNEY DISEASE ACCORDING TO BLOOD PRESSURE CATEGORIES IN DIABETIC PATIENTS : A POPULATION-BASED STUDY. Nephrology Dialysis Transplantation. 35(Supplement_3). 1 indexed citations
9.
Han, Junhee, et al.. (2020). Magnetic resonance elastography for evaluation of renal parenchyma in chronic kidney disease: a pilot study. La radiologia medica. 125(12). 1209–1215. 18 indexed citations
10.
Lee, Jun Young, Byoung Geun Han, Seung Ok Choi, et al.. (2019). Increased Delta Neutrophil Index Is Associated With Poor Prognosis in Cadaver Donor Kidney Transplantation. Transplantation Proceedings. 51(8). 2671–2675.
11.
Huh, Ji Hye, Jang‐Young Kim, Jang‐Young Kim, et al.. (2017). The fatty liver index as a predictor of incident chronic kidney disease in a 10-year prospective cohort study. PLoS ONE. 12(7). e0180951–e0180951. 49 indexed citations
12.
Huh, Ji Hye, Dhananjay Yadav, Jae Seok Kim, et al.. (2016). An association of metabolic syndrome and chronic kidney disease from a 10-year prospective cohort study. Metabolism. 67. 54–61. 77 indexed citations
13.
Kim, Jae Seok, Jae Won Yang, Jun Young Lee, et al.. (2014). Myeloma progression and urinary gammaglobulin affect the urinary cystatin C to diagnose acute kidney injury in multiple myeloma. Clinical Nephrology. 81(5). 345–349. 1 indexed citations
14.
Yang, Jae Won, Jae Seok Kim, Min-Keun Kim, et al.. (2013). The renoprotective effect of cGMP phosphodiesterase inhibitor and nitroprusside in a rat model of cyclosporin A-induced nephrotoxicity. Clinical Nephrology. 80(7). 53–62. 4 indexed citations
15.
Kim, Jae Seok, Min-Keun Kim, Jun Young Lee, et al.. (2012). The Effects of Proteinuria on Urinary Cystatin-C and Glomerular Filtration Rate Calculated by Serum Cystatin-C. Renal Failure. 34(6). 676–684. 11 indexed citations
16.
Yang, Jae Won, et al.. (2012). Serum T3 Level Can Predict Cardiovascular Events and All-Cause Mortality Rates in CKD Patients with Proteinuria. Renal Failure. 34(3). 364–372. 19 indexed citations
17.
Choi, Seung Ok, Jae Seok Kim, Jong In Lee, et al.. (2011). Membranoproliferative Glomerulonephritis Associated with Papillary Thyroid Carcinoma. Kidney Research and Clinical Practice. 30(2). 183–186. 2 indexed citations
18.
Kim, Jae Seok, et al.. (2007). A Case of Membranous Glomerulonephritis in a Patient with HIV Infection. Kidney Research and Clinical Practice. 26(6). 740–743. 2 indexed citations
19.
Kim, Min‐Soo, et al.. (2007). Comparison between Hemodialysis and Peritoneal Dialysis in Patients with End-stage Renal Disease and Liver Cirrhosis. Kidney Research and Clinical Practice. 26(6). 705–715. 1 indexed citations
20.
Kim, Kyoung‐Tae, Jin-Ho Kim, Hyuk-Chan Kwon, et al.. (2005). Clinical significance of chromosomal abnormality in multiple myeloma. The Korean Journal of Internal Medicine. 69(3). 304–312. 1 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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