Tae Joon Jun
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
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- Artificial Intelligence in Healthcare
Papers in
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- Machine Learning in Healthcare 6
- Adversarial Robustness in Machine Learning 4
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- ECG Monitoring and Analysis 4
- Co-authors
- Young‐Hak Kim (31 shared papers)Daeyoung Kim (14 shared papers)Jihoon Kweon (4 shared papers)Do‐Hyeun Kim (6 shared papers)Minh H. Nguyen (1 shared paper)Hee Jun Kang (17 shared papers)Yunha Kim (17 shared papers)Cherry Kim (3 shared papers)
- Journals
- Scientific Reports (7 papers)BMC Medical Informatics and Decision Making (3 papers)Computer Methods and Programs in Biomedicine (2 papers)JAMA Network Open (2 papers)International Journal of Surgery (2 papers)
- Partner nations
- South KoreaUnited StatesCanada
In The Last Decade
Tae Joon Jun
45 papers receiving 460 citations
Peers
Comparison fields: 5 of 83
- Health Informatics 31
- Health Information Management 29
- Cardiology and Cardiovascular Medicine 100
- Radiology, Nuclear Medicine and Imaging 99
- Computer Vision and Pattern Recognition 75
Countries citing papers authored by Tae Joon Jun
This map shows the geographic impact of Tae Joon Jun'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 Tae Joon Jun with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tae Joon Jun more than expected).
Fields of papers citing papers by Tae Joon Jun
This network shows the impact of papers produced by Tae Joon Jun. 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 Tae Joon Jun. The network helps show where Tae Joon Jun may publish in the future.
Co-authors
The 25 scholars most cited alongside Tae Joon Jun, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 52 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 56 | |
| 2 | 2016 | 45 | |
| 3 | 2018 | 33 | |
| 4 | 2021 | 32 | |
| 5 | 2021 | 27 | |
| 6 | 2018 | 25 | |
| 7 | 2020 | 23 | |
| 8 | 2021 | 21 | |
| 9 | 2024 | 16 | |
| 10 | 2019 | 16 | |
| 11 | 2017 | 13 | |
| 12 | 2023 | 13 | |
| 13 | 2021 | 11 | |
| 14 | 2019 | 11 | |
| 15 | 2024 | 9 | |
| 16 | 2023 | 9 | |
| 17 | 2016 | 9 | |
| 18 | 2019 | 9 | |
| 19 | 2024 | 8 | |
| 20 | 2023 | 8 |
About Tae Joon Jun
Tae Joon Jun is a scholar working on Artificial Intelligence, Cardiology and Cardiovascular Medicine, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Surgery, having authored 52 papers that have together received 470 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (6 papers), Retinal Imaging and Analysis (4 papers), Adversarial Robustness in Machine Learning (4 papers), ECG Monitoring and Analysis (4 papers), Digital Imaging for Blood Diseases (3 papers), Cloud Computing and Resource Management (3 papers), EEG and Brain-Computer Interfaces (3 papers) and Artificial Intelligence in Healthcare and Education (3 papers). The work is most often cited by research in Health Informatics (31 citations), Health Information Management (29 citations), Cardiology and Cardiovascular Medicine (100 citations), Radiology, Nuclear Medicine and Imaging (99 citations) and Computer Vision and Pattern Recognition (75 citations). Tae Joon Jun has collaborated with scholars based in South Korea, United States and Canada. Frequent co-authors include Young‐Hak Kim, Daeyoung Kim, Jihoon Kweon, Do‐Hyeun Kim, Minh H. Nguyen, Hee Jun Kang, Yunha Kim, Cherry Kim, Youngsub Eom and Wonjun Na. Their work appears in journals such as Scientific Reports, BMC Medical Informatics and Decision Making, Computer Methods and Programs in Biomedicine, JAMA Network Open and International Journal of Surgery.
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.