Youngtaek Hong

895 total citations
50 papers, 583 citations indexed

About

Youngtaek Hong is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Youngtaek Hong has authored 50 papers receiving a total of 583 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Radiology, Nuclear Medicine and Imaging, 18 papers in Biomedical Engineering and 16 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Youngtaek Hong's work include Cardiac Imaging and Diagnostics (17 papers), Advanced X-ray and CT Imaging (15 papers) and Radiomics and Machine Learning in Medical Imaging (12 papers). Youngtaek Hong is often cited by papers focused on Cardiac Imaging and Diagnostics (17 papers), Advanced X-ray and CT Imaging (15 papers) and Radiomics and Machine Learning in Medical Imaging (12 papers). Youngtaek Hong collaborates with scholars based in South Korea, United States and China. Youngtaek Hong's co-authors include Young Lan Kwak, Young Hwan Park, Young Jun Oh, Hyuk‐Jae Chang, Robert W.M. Frater, Helen Ki Shinn, Toshihito Tsubo, Paul G. Loubser, Ho‐Young Kwak and Yeonggul Jang and has published in prestigious journals such as Journal of the American College of Cardiology, PLoS ONE and Anesthesiology.

In The Last Decade

Youngtaek Hong

45 papers receiving 569 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Youngtaek Hong South Korea 14 237 199 184 176 134 50 583
Piotr Lipiec Poland 15 415 1.8× 225 1.1× 239 1.3× 119 0.7× 77 0.6× 114 744
Tomáš Kovárník Czechia 14 182 0.8× 338 1.7× 112 0.6× 115 0.7× 242 1.8× 69 603
Takashi Muro Japan 15 547 2.3× 259 1.3× 426 2.3× 124 0.7× 62 0.5× 51 759
Terry D. Bauch United States 14 639 2.7× 147 0.7× 72 0.4× 91 0.5× 49 0.4× 28 857
Benoy N. Shah United Kingdom 16 574 2.4× 164 0.8× 374 2.0× 200 1.1× 87 0.6× 75 840
Lazar Velicki Serbia 15 413 1.7× 181 0.9× 79 0.4× 84 0.5× 101 0.8× 89 656
Arcangelo D’Errico Italy 11 652 2.8× 212 1.1× 316 1.7× 90 0.5× 46 0.3× 17 883
Svein Arne Aase Norway 13 709 3.0× 94 0.5× 530 2.9× 77 0.4× 115 0.9× 29 886
Andrew Kelion United Kingdom 15 926 3.9× 649 3.3× 992 5.4× 108 0.6× 290 2.2× 55 1.6k
RM Lang United States 8 782 3.3× 149 0.7× 288 1.6× 145 0.8× 49 0.4× 24 906

Countries citing papers authored by Youngtaek Hong

Since Specialization
Citations

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

Fields of papers citing papers by Youngtaek Hong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Youngtaek Hong. 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 Youngtaek Hong. The network helps show where Youngtaek Hong may publish in the future.

Co-authorship network of co-authors of Youngtaek Hong

This figure shows the co-authorship network connecting the top 25 collaborators of Youngtaek Hong. A scholar is included among the top collaborators of Youngtaek Hong 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 Youngtaek Hong. Youngtaek Hong 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.
Park, Jiesuck, Yeonyee E. Yoon, Yeonggul Jang, et al.. (2025). Artificial intelligence-enhanced comprehensive assessment of the aortic valve stenosis continuum in echocardiography. EBioMedicine. 112. 105560–105560. 4 indexed citations
2.
Hong, Youngtaek, Yun Jang, Ran Heo, et al.. (2025). Predicting categories of coronary artery calcium scores from chest X-ray images using deep learning. Journal of cardiovascular computed tomography. 19(3). 331–339. 1 indexed citations
3.
Moon, Inki, Yeonggul Jang, Hong‐Mi Choi, et al.. (2025). Artificial Intelligence-Enhanced Analysis of Echocardiography-Based Radiomic Features for Myocardial Hypertrophy Detection and Etiology Differentiation. Circulation Cardiovascular Imaging. 18(5). e017436–e017436.
4.
Ha, Seongmin, Yeonggul Jang, Byoung Kwon Lee, et al.. (2024). Simultaneous Viability Assessment and Invasive Coronary Angiography Using a Therapeutic CT System in Chronic Myocardial Infarction Patients. Yonsei Medical Journal. 65(5). 257–257. 1 indexed citations
5.
6.
Hong, Youngtaek, et al.. (2024). Fully Convolutional Hybrid Fusion Network With Heterogeneous Representations for Identification of S1 and S2 From Phonocardiogram. IEEE Journal of Biomedical and Health Informatics. 28(12). 7151–7163. 2 indexed citations
7.
Jung, Sung‐Hee, Yeonyee E. Yoon, Yeonggul Jang, et al.. (2024). Artificial intelligence-enhanced automation for M-mode echocardiographic analysis: ensuring fully automated, reliable, and reproducible measurements. The International Journal of Cardiovascular Imaging. 40(6). 1245–1256. 2 indexed citations
8.
Hong, Youngtaek, et al.. (2024). Improving the Reproducibility of Computed Tomography Radiomic Features Using an Enhanced Hierarchical Feature Synthesis Network. IEEE Access. 12. 27648–27660. 4 indexed citations
9.
Lee, Seul Bi, Youngtaek Hong, Yeon Jin Cho, et al.. (2024). Enhancing Radiomics Reproducibility: Deep Learning-Based Harmonization of Abdominal Computed Tomography (CT) Images. Bioengineering. 11(12). 1212–1212. 1 indexed citations
10.
11.
Jang, Yeonggul, et al.. (2020). Generation of High-Resolution Chest X-rays using Multi-scale Conditional Generative Adversarial Network with Attention. Journal of Broadcast Engineering. 25(1). 1–12. 1 indexed citations
12.
Hong, Youngtaek, Frédéric Commandeur, Sebastien Cadet, et al.. (2019). Deep learning-based stenosis quantification from coronary CT angiography. PubMed. 10949. 88–88. 42 indexed citations
13.
Hong, Youngtaek, et al.. (2014). Adjusting Nonresponse Bias of RDD Telephone Survey: Case Study of Poll Data for 2014 Local Election. 15(4). 33–60.
14.
Shinn, Helen Ki, et al.. (2006). The effect of skin surface warming during anesthesia preparation on preventing redistribution hypothermia in the early operative period of off-pump coronary artery bypass surgery. European Journal of Cardio-Thoracic Surgery. 29(3). 343–347. 53 indexed citations
15.
Na, Sungwon, et al.. (2006). Effects of milrinone on blood flow of the Y-graft composed with the radial and the internal thoracic artery in patients with coronary artery disease☆. European Journal of Cardio-Thoracic Surgery. 30(2). 324–328. 6 indexed citations
16.
Kwak, Young Lan, Young Jun Oh, Simon Jung, et al.. (2004). Change in right ventricular function during off-pump coronary artery bypass graft surgery. European Journal of Cardio-Thoracic Surgery. 25(4). 572–577. 29 indexed citations
17.
Koo, Bon‐Nyeo, Hae Keum Kil, Yu Seob Shin, Jianxin Song, & Youngtaek Hong. (2004). The clinical effects of intrathecal mgso4 on spinal anesthesia and postoperative epidural analgesia in total knee replacement. Regional Anesthesia & Pain Medicine. 29. 11–11. 4 indexed citations
18.
19.
Koo, Bon‐Nyeo, Hae Keum Kil, Young-Soo Shin, Jong Wook Song, & Youngtaek Hong. (2004). The clinical effects of intrathecal MgSO4 on spinal anesthesia and postoperative epidural analgesia in total knee replacement. Regional Anesthesia & Pain Medicine. 29(Sup 2). 11–11. 2 indexed citations
20.
Hong, Youngtaek, et al.. (1999). Doppler Study on Pulmonary Venous Flow in the Human Fetus. Fetal Diagnosis and Therapy. 14(2). 86–91. 14 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Piotr Lipiec Breakdown of academic impact, for papers by Tomáš Kovárník Breakdown of academic impact, for papers by Takashi Muro Breakdown of academic impact, for papers by Terry D. Bauch Breakdown of academic impact, for papers by Benoy N. Shah Breakdown of academic impact, for papers by Lazar Velicki Breakdown of academic impact, for papers by Arcangelo D’Errico Breakdown of academic impact, for papers by Svein Arne Aase Breakdown of academic impact, for papers by Andrew Kelion Breakdown of academic impact, for papers by RM Lang
Rankless by CCL
2026