Oyeon Kwon

1.2k total citations · 2 hit papers
11 papers, 835 citations indexed

About

Oyeon Kwon is a scholar working on Epidemiology, Artificial Intelligence and Emergency Medicine. According to data from OpenAlex, Oyeon Kwon has authored 11 papers receiving a total of 835 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Epidemiology, 6 papers in Artificial Intelligence and 4 papers in Emergency Medicine. Recurrent topics in Oyeon Kwon's work include Sepsis Diagnosis and Treatment (6 papers), Machine Learning in Healthcare (5 papers) and Emergency and Acute Care Studies (3 papers). Oyeon Kwon is often cited by papers focused on Sepsis Diagnosis and Treatment (6 papers), Machine Learning in Healthcare (5 papers) and Emergency and Acute Care Studies (3 papers). Oyeon Kwon collaborates with scholars based in South Korea, Kazakhstan and Singapore. Oyeon Kwon's co-authors include Min-Ho Lee, Seong‐Whan Lee, Cuntai Guan, John Williamson, Siamac Fazli, Young-Eun Lee, Hwa Jin Cho, Yeha Lee, Hyunho Park and Joon‐myoung Kwon and has published in prestigious journals such as Critical Care Medicine, IEEE Transactions on Neural Networks and Learning Systems and Resuscitation.

In The Last Decade

Oyeon Kwon

11 papers receiving 823 citations

Hit Papers

align trajectories

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.

EEG dataset and OpenBMI toolbox for three BCI paradigms: an investigation into BCI illiteracy

2019 381 citations Min-Ho Lee, Oyeon Kwon et al. GigaScience profile →
Subject-Independent Brain–Computer Interfaces Based on Deep Convolutional Neural Networks

2019 253 citations Oyeon Kwon, Min-Ho Lee et al. IEEE Transactions on Neural Networks and Learning Systems profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Oyeon Kwon South Korea	7	589	272	198	129	124	11	835
Andrey Eliseyev France	13	247 0.4×	96 0.4×	30 0.2×	41 0.3×	23 0.2×	22	606
Mark Homer United States	10	332 0.6×	297 1.1×	138 0.7×	37 0.3×	23 0.2×	16	931
Franz Fürbass Austria	15	406 0.7×	69 0.3×	23 0.1×	77 0.6×	7 0.1×	30	540
Louis Mayaud France	14	202 0.3×	45 0.2×	18 0.1×	139 1.1×	18 0.1×	21	523
Ruhi Mahajan United States	14	487 0.8×	83 0.3×	34 0.2×	45 0.3×	54 0.4×	29	738
Tim Bonnici Bulgaria	4	133 0.2×	46 0.2×	28 0.1×	64 0.5×	16 0.1×	7	469
Wala Saadeh Pakistan	17	228 0.4×	88 0.3×	164 0.8×	23 0.2×	18 0.1×	56	868
Syed Anas Imtiaz United Kingdom	17	298 0.5×	34 0.1×	62 0.3×	44 0.3×	23 0.2×	37	913
Morteza Zabihi Finland	11	314 0.5×	23 0.1×	18 0.1×	75 0.6×	7 0.1×	21	663
Arvind Balasubramanian United States	8	111 0.2×	30 0.1×	22 0.1×	70 0.5×	17 0.1×	18	450

Countries citing papers authored by Oyeon Kwon

Since Specialization

Citations

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

Fields of papers citing papers by Oyeon Kwon

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Oyeon Kwon

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

All Works

Sort: Min cites: Since: Top N: Style:

11 of 11 papers shown

1.

Ko, Ryoung‐Eun, Oyeon Kwon, Hwa Jin Cho, et al.. (2022). Quick Sequential Organ Failure Assessment Score and the Modified Early Warning Score for Predicting Clinical Deterioration in General Ward Patients Regardless of Suspected Infection. Journal of Korean Medical Science. 37(16). e122–e122. 6 indexed citations

2.

Kwon, Oyeon, Sunghoon Joo, Yeha Lee, et al.. (2022). Evaluating the Risk of Paroxysmal Atrial Fibrillation in Noncardioembolic Ischemic Stroke Using Artificial Intelligence-Enabled ECG Algorithm. Frontiers in Cardiovascular Medicine. 9. 865852–865852. 6 indexed citations

3.

Park, Seong Jong, Hwa Jin Cho, Oyeon Kwon, et al.. (2021). Development and validation of a deep-learning-based pediatric early warning system: A single-center study. Biomedical Journal. 45(1). 155–168. 17 indexed citations

4.

Lee, Yeon Joo, Hwa Jin Cho, Oyeon Kwon, et al.. (2021). A multicentre validation study of the deep learning-based early warning score for predicting in-hospital cardiac arrest in patients admitted to general wards. Resuscitation. 163. 78–85. 32 indexed citations

5.

Cho, Hwa Jin, Oyeon Kwon, Joon‐myoung Kwon, et al.. (2020). Detecting Patient Deterioration Using Artificial Intelligence in a Rapid Response System. Critical Care Medicine. 48(4). e285–e289. 50 indexed citations

6.

Cho, Hwa Jin, Oyeon Kwon, Joon‐myoung Kwon, et al.. (2020). Artificial intelligence algorithm to predict the need for critical care in prehospital emergency medical services. Scandinavian Journal of Trauma Resuscitation and Emergency Medicine. 28(1). 17–17. 76 indexed citations

7.

Kwon, Oyeon, et al.. (2020). Graph Convolutional Networks-Based Noisy Data Imputation in Electronic Health Record. Critical Care Medicine. 48(11). e1106–e1111. 11 indexed citations

8.

Lee, Min-Ho, Oyeon Kwon, Young-Eun Lee, et al.. (2019). EEG dataset and OpenBMI toolbox for three BCI paradigms: an investigation into BCI illiteracy. GigaScience. 8(5). 381 indexed citations breakdown →

9.

Cho, Hwa Jin, et al.. (2019). Improving the Performance of a Neural Network for Early Prediction of Sepsis. Computing in Cardiology Conference. 1–4. 1 indexed citations

10.

Cho, Hwa Jin, et al.. (2019). Improving the Performance of a Neural Network for Early Prediction of Sepsis. Computing in cardiology. 45. 2 indexed citations

11.

Kwon, Oyeon, Min-Ho Lee, Cuntai Guan, & Seong‐Whan Lee. (2019). Subject-Independent Brain–Computer Interfaces Based on Deep Convolutional Neural Networks. IEEE Transactions on Neural Networks and Learning Systems. 31(10). 3839–3852. 253 indexed citations breakdown →

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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