Min Su Lee

639 total citations
35 papers, 486 citations indexed

About

Min Su Lee is a scholar working on Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine and Biomedical Engineering. According to data from OpenAlex, Min Su Lee has authored 35 papers receiving a total of 486 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Radiology, Nuclear Medicine and Imaging, 8 papers in Cardiology and Cardiovascular Medicine and 7 papers in Biomedical Engineering. Recurrent topics in Min Su Lee's work include Cardiac Imaging and Diagnostics (11 papers), Indoor and Outdoor Localization Technologies (5 papers) and Coronary Interventions and Diagnostics (4 papers). Min Su Lee is often cited by papers focused on Cardiac Imaging and Diagnostics (11 papers), Indoor and Outdoor Localization Technologies (5 papers) and Coronary Interventions and Diagnostics (4 papers). Min Su Lee collaborates with scholars based in South Korea, United States and Ethiopia. Min Su Lee's co-authors include Sangyoon Oh, Byoung‐Tak Zhang, Eun Ju Chun, Sang Il Choi, Chan Gook Park, Kil Joong Kim, Woong‐Yang Park, Jeong A. Kim, Eunha Oh and Byoung‐Tak Zhang and has published in prestigious journals such as Scientific Reports, Clinical Cancer Research and American Journal of Roentgenology.

In The Last Decade

Min Su Lee

34 papers receiving 470 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Min Su Lee South Korea 14 102 87 80 77 75 35 486
Ioannis Valavanis Greece 14 168 1.6× 43 0.5× 174 2.2× 52 0.7× 71 0.9× 34 700
Jingyang Gao China 11 156 1.5× 38 0.4× 163 2.0× 78 1.0× 26 0.3× 55 682
Jiwoong Jeong United States 12 244 2.4× 52 0.6× 168 2.1× 127 1.6× 43 0.6× 34 609
K. Gopalakrishna Prabhu India 16 179 1.8× 87 1.0× 147 1.8× 180 2.3× 13 0.2× 40 728
Sanjay Saxena India 18 379 3.7× 31 0.4× 258 3.2× 113 1.5× 52 0.7× 78 952
Rusi Chen China 9 84 0.8× 199 2.3× 109 1.4× 36 0.5× 12 0.2× 61 562
Junhan Zhao United States 13 42 0.4× 25 0.3× 66 0.8× 28 0.4× 127 1.7× 52 632
Philipp Seegerer Germany 6 63 0.6× 25 0.3× 107 1.3× 33 0.4× 78 1.0× 7 355
Shayan Shams United States 15 112 1.1× 57 0.7× 220 2.8× 83 1.1× 21 0.3× 36 637
Shuo Zhou China 11 40 0.4× 81 0.9× 41 0.5× 52 0.7× 42 0.6× 42 459

Countries citing papers authored by Min Su Lee

Since Specialization
Citations

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

Fields of papers citing papers by Min Su Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Min Su Lee. 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 Min Su Lee. The network helps show where Min Su Lee may publish in the future.

Co-authorship network of co-authors of Min Su Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Min Su Lee. A scholar is included among the top collaborators of Min Su Lee 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 Min Su Lee. Min Su Lee 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.
Lee, Min Su, et al.. (2020). Mec1 Modulates Interhomolog Crossover and Interplays with Tel1 at Post Double-Strand Break Stages. Journal of Microbiology and Biotechnology. 30(3). 469–475. 4 indexed citations
2.
Lee, Min Su, et al.. (2016). Identification of Angiogenesis Rich-Viable Myocardium using RGD Dimer based SPECT after Myocardial Infarction. Scientific Reports. 6(1). 27520–27520. 9 indexed citations
3.
Lee, Min Su, et al.. (2015). Use of Multiple Wearable Inertial Sensors in Human Localization. 1037–1042. 4 indexed citations
4.
Chun, Eun Ju, et al.. (2015). Coronary CT angiography findings based on smoking status: Do ex-smokers and never-smokers share a low probability of developing coronary atherosclerosis?. International journal of cardiac imaging. 31(S2). 169–176. 5 indexed citations
5.
Lee, Min Su, et al.. (2015). A pedestrian dead-reckoning system that considers the heel-strike and toe-off phases when using a foot-mounted IMU. Measurement Science and Technology. 27(1). 15702–15702. 33 indexed citations
6.
Chun, Eun Ju, et al.. (2014). Grade-response relationship between blood pressure and severity of coronary atherosclerosis in asymptomatic adults: assessment with coronary CT angiography. International journal of cardiac imaging. 30(S2). 105–112. 9 indexed citations
7.
Han, Jeong Hee, et al.. (2014). Sodium [18F]Fluoride PET/CT in Myocardial Infarction. Molecular Imaging and Biology. 17(2). 214–221. 10 indexed citations
8.
9.
Kim, Jeong A., Eun Ju Chun, Min Su Lee, Kil Joong Kim, & Sang Il Choi. (2013). Relationship between amount of cigarette smoking and coronary atherosclerosis on coronary CTA in asymptomatic individuals. International journal of cardiac imaging. 29(S1). 21–28. 23 indexed citations
10.
Lee, Kyung Hee, Sang Il Choi, Eun Ju Chun, et al.. (2012). Aborted Myocardial Infarction: Evaluation of Changes in Area at Risk, Late Gadolinium Enhancement, and Perfusion Over Time and Comparison With Overt Myocardial Infarction. American Journal of Roentgenology. 199(2). 328–335. 7 indexed citations
11.
Lee, Min Su, et al.. (2010). Evaluation of a Pedestrian Walking Status Awareness Algorithm for a Pedestrian Dead Reckoning. Seoul National University Open Repository (Seoul National University). 2280–2284. 6 indexed citations
12.
Lee, Min Su, Jeff C. Ko, In Hye Lee, et al.. (2010). EFFECTS OF ANESTHETIC PROTOCOL ON NORMAL CANINE BRAIN UPTAKE OF18F-FDG ASSESSED BY PET/CT. Veterinary Radiology & Ultrasound. 51(2). 130–5. 19 indexed citations
13.
Lee, Min Su, et al.. (2010). IMAGING DIAGNOSIS-FDG-PET/CT OF A CANINE SPLENIC PLASMA CELL TUMOR. Veterinary Radiology & Ultrasound. 51(2). 145–7. 5 indexed citations
14.
Oh, Sangyoon, Min Su Lee, & Byoung‐Tak Zhang. (2010). Ensemble Learning with Active Example Selection for Imbalanced Biomedical Data Classification. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 8(2). 316–325. 77 indexed citations
15.
Lee, Min Su, Eun Ju Chun, Kil Joong Kim, et al.. (2010). Reproducibility in the assessment of noncalcified coronary plaque with 256-slice multi-detector CT and automated plaque analysis software. International journal of cardiac imaging. 26(S2). 237–244. 13 indexed citations
16.
Nam, Do‐Hyun, Hye-Min Jeon, Mi‐Hyun Kim, et al.. (2008). Activation of Notch Signaling in a Xenograft Model of Brain Metastasis. Clinical Cancer Research. 14(13). 4059–4066. 61 indexed citations
17.
Lee, Min Su, Eunha Oh, Federico Kalinec, et al.. (2008). Characterization of biological effect of 1763 MHz radiofrequency exposure on auditory hair cells. International Journal of Radiation Biology. 84(11). 909–915. 25 indexed citations
18.
Lee, Min Su, et al.. (2008). Molecular responses of Jurkat T-cells to 1763 MHz radiofrequency radiation. International Journal of Radiation Biology. 84(9). 734–741. 28 indexed citations
19.
Lee, Min Su, et al.. (2007). Prediction of the Exposure to 1763MHz Radiofrequency Radiation Based on Gene Expression Patterns. Genomics & Informatics. 5(3). 102–106.
20.
Jeong, Jun Young, Min Su Lee, Jeong Hee Kim, et al.. (2002). The Study of Coronary Spasm by Follow-up Coronary Angiography in Variant Angina. Sunhwan'gi. 32(9). 791–791. 4 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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