Ju Han Kim

8.7k total citations · 1 hit paper
492 papers, 5.6k citations indexed

About

Ju Han Kim is a scholar working on Cardiology and Cardiovascular Medicine, Surgery and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Ju Han Kim has authored 492 papers receiving a total of 5.6k indexed citations (citations by other indexed papers that have themselves been cited), including 309 papers in Cardiology and Cardiovascular Medicine, 250 papers in Surgery and 150 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Ju Han Kim's work include Coronary Interventions and Diagnostics (163 papers), Acute Myocardial Infarction Research (159 papers) and Cardiac Imaging and Diagnostics (145 papers). Ju Han Kim is often cited by papers focused on Coronary Interventions and Diagnostics (163 papers), Acute Myocardial Infarction Research (159 papers) and Cardiac Imaging and Diagnostics (145 papers). Ju Han Kim collaborates with scholars based in South Korea, United States and Ethiopia. Ju Han Kim's co-authors include Young Joon Hong, Youngkeun Ahn, Myung Ho Jeong, Jeong Gwan Cho, Doo Sun Sim, Myung Ho Jeong, Jung Chaee Kang, Hyung Wook Park, Kye Hun Kim and Jong Chun Park and has published in prestigious journals such as JAMA, Circulation and Journal of the American College of Cardiology.

In The Last Decade

Ju Han Kim

452 papers receiving 5.4k citations

Hit Papers

The 2022 focused update of the 2018 Korean Hypertension S... 2023 2026 2024 2025 2023 25 50 75

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ju Han Kim South Korea 36 2.8k 1.9k 1.1k 726 689 492 5.6k
Myung Ho Jeong South Korea 41 3.7k 1.3× 2.8k 1.5× 1.6k 1.5× 825 1.1× 825 1.2× 514 7.0k
Chi‐Hang Lee Singapore 39 2.3k 0.8× 2.2k 1.2× 776 0.7× 1.4k 1.9× 760 1.1× 294 6.1k
Michael Williams New Zealand 42 2.4k 0.8× 1.4k 0.7× 659 0.6× 1.1k 1.5× 651 0.9× 229 6.2k
Lino Gonçalves Portugal 28 3.4k 1.2× 1.4k 0.7× 1.1k 1.0× 371 0.5× 848 1.2× 321 5.1k
Scott Kinlay United States 42 2.6k 0.9× 2.7k 1.4× 1.0k 0.9× 1.1k 1.5× 476 0.7× 150 5.8k
Junya Ako Japan 41 4.0k 1.4× 3.0k 1.5× 1.3k 1.2× 1.5k 2.0× 532 0.8× 490 7.3k
Myeong‐Chan Cho South Korea 40 4.4k 1.6× 1.7k 0.9× 1.1k 1.0× 445 0.6× 652 0.9× 329 6.2k
Gianluca Campo Italy 46 5.1k 1.8× 3.5k 1.8× 1.4k 1.3× 1.1k 1.5× 778 1.1× 303 7.7k
Márcio Sommer Bittencourt Brazil 33 2.3k 0.8× 1.7k 0.9× 1.8k 1.7× 929 1.3× 982 1.4× 250 6.4k
Francesco Fedele Italy 40 4.2k 1.5× 1.3k 0.7× 1.1k 1.0× 1.5k 2.0× 545 0.8× 249 6.1k

Countries citing papers authored by Ju Han Kim

Since Specialization
Citations

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

Fields of papers citing papers by Ju Han Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ju Han Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Ju Han Kim. A scholar is included among the top collaborators of Ju Han 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 Ju Han Kim. Ju Han 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
2.
Kim, Hyun‐Jin, Yonggu Lee, Jeong‐Hun Shin, et al.. (2025). Impact of Clinic Blood Pressure Target on the Prevalence and Predictors of Masked Uncontrolled Hypertension and White-Coat Uncontrolled Hypertension. Journal of Korean Medical Science. 40(24). e117–e117.
4.
Sim, Doo Sun, Dae Young Hyun, Young Joon Hong, et al.. (2024). Clinical Outcome after Everolimus-Eluting Stent Implantation for Small Vessel Coronary Artery Disease: XIENCE Asia Small Vessel Study. Chonnam Medical Journal. 60(1). 78–78.
5.
6.
Park, Sungha, Jinho Shin, Sang‐Hyun Ihm, et al.. (2023). Resistant hypertension: consensus document from the Korean society of hypertension. Clinical Hypertension. 29(1). 30–30. 7 indexed citations
7.
Song, Jiyeon, Jae Yeong Cho, Kye Hun Kim, et al.. (2023). Predictors of Progression of Tricuspid Regurgitation in Patients with Persistent Atrial Fibrillation. Chonnam Medical Journal. 59(1). 70–70. 2 indexed citations
8.
Oh, Seok, Dae Young Hyun, Sang‐Geon Cho, et al.. (2023). Case report: A fatal case of myocardial infarction due to myocardial bridge and concomitant vasospasm: the role of stress gated SPECT. Frontiers in Cardiovascular Medicine. 10. 1188095–1188095.
9.
Oh, Seok Kyu, Min Chul Kim, Doo Sun Sim, et al.. (2023). Time to presentation and mortality outcomes among patients with diabetes and acute myocardial infarction. The Korean Journal of Internal Medicine. 39(1). 110–122.
10.
Cho, Kyung Hoon, Min‐Ho Shin, Min Chul Kim, et al.. (2022). Prognostic Value of Baseline Neutrophil-to-Lymphocyte Ratio Combined With Anemia in Patients With ST-Segment Elevation Myocardial Infarction: A Nationwide Prospective Cohort Study. Journal of Lipid and Atherosclerosis. 11(2). 147–147. 5 indexed citations
11.
Cho, Kyung Hoon, Min Chul Kim, Eun Ho Choo, et al.. (2022). Impact of Low Baseline Low‐Density Lipoprotein Cholesterol on Long‐Term Postdischarge Cardiovascular Outcomes in Patients With Acute Myocardial Infarction. Journal of the American Heart Association. 11(17). e025958–e025958. 4 indexed citations
12.
Bai, Liyan, Myung Ho Jeong, Joon Ho Ahn, et al.. (2021). Higher Long-Term Mortality in Patients with Non-ST-Elevation Myocardial Infarction than ST-Elevation Myocardial Infarction after Discharge. Yonsei Medical Journal. 62(5). 400–400. 12 indexed citations
13.
Cho, Sang‐Geon, et al.. (2020). Diagnostic Value of Lesion-specific Measurement of Myocardial Blood Flow Using Hybrid PET/CT. PubMed. 28(2). 94–94. 2 indexed citations
14.
Kim, Min Chul, Youngkeun Ahn, Kyung Hoon Cho, et al.. (2020). Image of Statin-Induced Rhabdomyolysis. Korean Circulation Journal. 50(8). 738–738.
15.
Kim, Min Chul, In‐Soo Kim, Myung Ho Jeong, et al.. (2019). Incidence of cardiac death and recurrent stent thrombosis after treatment for angiographically confirmed stent thrombosis. Journal of Cardiology. 74(3). 267–272. 9 indexed citations
16.
Kim, Yongcheol, Youngkeun Ahn, Inna Kim, et al.. (2018). Feasibility of Coronary Angiography and Percutaneous Coronary Intervention via Left Snuffbox Approach. Korean Circulation Journal. 48(12). 1120–1120. 66 indexed citations
17.
Cho, Jae Yeong, Kye Hun Kim, Ji Eun Song, et al.. (2017). Predictors of Left Ventricular Functional Recovery and Their Impact on Clinical Outcomes in Patients With Newly Diagnosed Dilated Cardiomyopathy and Heart Failure. Heart Lung and Circulation. 27(1). 41–49. 7 indexed citations
18.
Kim, Joon Young, Myung Ho Jeong, Jang Hyun Cho, et al.. (2008). Predictors of Hospital Mortality for Patients With Acute Myocardial Infarction That was Treated With an Artificial Ventilator and/or an Intra-aortic Balloon Pump. Korean Circulation Journal. 38(5). 257–257.
19.
20.
Jeong, Myung Ho, et al.. (2003). Long-term clinical outcomes in diabetics after coronary artery bypass surgery and coronary stenting.. The Korean Journal of Internal Medicine. 65(2). 160–167. 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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