Oyeon Kwon

1.3k citations
11 papers · 898 · 2 hit papers · h-index 8

Impact in

Papers in

Oyeon Kwon

11 papers receiving 885 citations

Oyeon Kwon's Hit Papers

Subject-Independent Brain–Computer Interfaces Based on Deep Convolutional Neural Networks 2019 · 268 citations
2680+2+4Years since publication100200300400

Peers

Oyeon Kwon
Comparison fields: 5 of 62
  • Cognitive Neuroscience 628
  • Health Informatics 38
  • Human-Computer Interaction 127
  • Cellular and Molecular Neuroscience 269
  • Emergency Medicine 70
Replace Andrey Eliseyev with:
Andrey Eliseyev France
Syed Khairul Bashar United States
Ruhi Mahajan United States
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Syed Anas Imtiaz United Kingdom
Morteza Zabihi Finland
Viswam Nathan United States
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Citations per field
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Citations per year

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-authors

The 25 scholars most cited alongside Oyeon Kwon, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Oyeon Kwon Line = papers co-authored together Oyeon Kwon links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1
EEG dataset and OpenBMI toolbox for three BCI paradigms: an investigation into BCI illiteracy
Hit paper breakdown →
2019411
2
Subject-Independent Brain–Computer Interfaces Based on Deep Convolutional Neural Networks
Hit paper breakdown →
2019268
3 202086
4 202051
5 202135
6 202119
7 202012
8 20227
9 20226
10 20192
11 20191

About Oyeon Kwon

Oyeon Kwon is a scholar working on Epidemiology, Artificial Intelligence, Cognitive Neuroscience, Cellular and Molecular Neuroscience and Cardiology and Cardiovascular Medicine, having authored 11 papers that have together received 898 indexed citations. Recurring topics across this work include Sepsis Diagnosis and Treatment (6 papers), EEG and Brain-Computer Interfaces (2 papers), Machine Learning in Healthcare (2 papers), Hydrological Forecasting Using AI (1 paper), Neuroscience and Neural Engineering (1 paper), Emergency and Acute Care Studies (1 paper), Digital Imaging for Blood Diseases (1 paper) and Edcuational Technology Systems (1 paper). The work is most often cited by research in Cognitive Neuroscience (628 citations), Health Informatics (38 citations), Human-Computer Interaction (127 citations), Cellular and Molecular Neuroscience (269 citations) and Emergency Medicine (70 citations). Oyeon Kwon has collaborated with scholars based in South Korea, Kazakhstan and Singapore. Frequent co-authors include Min-Ho Lee, Seong–Whan Lee, Cuntai Guan, Young-Eun Lee, John Williamson, Siamac Fazli, Yeha Lee, Hwa Jin Cho, Hyunho Park and Joon‐myoung Kwon. Their work appears in journals such as Critical Care Medicine, IEEE Transactions on Neural Networks and Learning Systems, Frontiers in Cardiovascular Medicine, Journal of Korean Medical Science and Resuscitation.

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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