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 11
- Adversarial Robustness in Machine Learning 3
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- ECG Monitoring and Analysis 5
- Antiplatelet Therapy and Cardiovascular Diseases 3
- Co-authors
- Young‐Hak Kim (29 shared papers)Daeyoung Kim (11 shared papers)Jihoon Kweon (3 shared papers)Do‐Hyeun Kim (5 shared papers)Minh H. Nguyen (1 shared paper)Hee Jun Kang (17 shared papers)Youngsub Eom (3 shared papers)Cherry Kim (3 shared papers)
- Journals
- Scientific Reports (7 papers)BMC Medical Informatics and Decision Making (3 papers)International Journal of Surgery (2 papers)Computer Methods and Programs in Biomedicine (2 papers)Health Care Management Science (1 paper)
- Partner nations
- South KoreaUnited KingdomUnited States
In The Last Decade
Tae Joon Jun
36 papers receiving 388 citations
Peers
Comparison fields: 5 of 84
- Health Informatics 29
- Health Information Management 33
- Cardiology and Cardiovascular Medicine 103
- Radiology, Nuclear Medicine and Imaging 99
- Computational Mathematics 2
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 46 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 48 | |
| 2 | 2016 | 43 | |
| 3 | 2021 | 29 | |
| 4 | 2018 | 28 | |
| 5 | 2021 | 27 | |
| 6 | 2018 | 25 | |
| 7 | 2021 | 21 | |
| 8 | 2020 | 20 | |
| 9 | 2019 | 16 | |
| 10 | 2017 | 12 | |
| 11 | 2023 | 10 | |
| 12 | 2019 | 10 | |
| 13 | 2024 | 9 | |
| 14 | 2021 | 9 | |
| 15 | 2023 | 8 | |
| 16 | 2016 | 8 | |
| 17 | 2019 | 8 | |
| 18 | 2024 | 7 | |
| 19 | 2023 | 7 | |
| 20 | 2022 | 6 |
About Tae Joon Jun
Tae Joon Jun is a scholar working on Artificial Intelligence, Cardiology and Cardiovascular Medicine, Surgery, Computer Vision and Pattern Recognition and Health Information Management, having authored 46 papers that have together received 397 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (11 papers), Artificial Intelligence in Healthcare (5 papers), ECG Monitoring and Analysis (5 papers), Lipoproteins and Cardiovascular Health (5 papers), Artificial Intelligence in Healthcare and Education (4 papers), Retinal Imaging and Analysis (4 papers), Antiplatelet Therapy and Cardiovascular Diseases (3 papers) and Adversarial Robustness in Machine Learning (3 papers). The work is most often cited by research in Health Informatics (29 citations), Health Information Management (33 citations), Cardiology and Cardiovascular Medicine (103 citations), Radiology, Nuclear Medicine and Imaging (99 citations) and Computational Mathematics (2 citations). Tae Joon Jun has collaborated with scholars based in South Korea, United Kingdom and United States. Frequent co-authors include Young‐Hak Kim, Daeyoung Kim, Jihoon Kweon, Do‐Hyeun Kim, Minh H. Nguyen, Hee Jun Kang, Youngsub Eom, Cherry Kim, Yunha Kim and Wonjun Na. Their work appears in journals such as Scientific Reports, BMC Medical Informatics and Decision Making, International Journal of Surgery, Computer Methods and Programs in Biomedicine and Health Care Management Science.
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.