Hee Jun Kang
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
- Otorhinolaryngology top 10%
- Sinusitis and nasal conditions
Papers in
-
- Machine Learning in Healthcare 8
- Co-authors
- Cheng-Xian Lin (3 shared papers)M. A. Ebadian (3 shared papers)Young‐Hak Kim (19 shared papers)Dong Hyun Yang (7 shared papers)Duy-Tang Hoang (1 shared paper)June‐Goo Lee (2 shared papers)Tae Joon Jun (17 shared papers)Junsang Moon (1 shared paper)
- Journals
- Scientific Reports (5 papers)BMC Medical Informatics and Decision Making (3 papers)Journal of Korean Medical Science (2 papers)Nonlinear Dynamics (2 papers)International Journal of Cardiology (1 paper)
- Partner nations
- South KoreaUnited StatesChina
In The Last Decade
Hee Jun Kang
37 papers receiving 545 citations
Peers
Comparison fields: 5 of 99
- Health Informatics 30
- Otorhinolaryngology 34
- Radiology, Nuclear Medicine and Imaging 150
- Health Information Management 27
- Mechanical Engineering 102
Countries citing papers authored by Hee Jun Kang
This map shows the geographic impact of Hee Jun Kang'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 Hee Jun Kang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hee Jun Kang more than expected).
Fields of papers citing papers by Hee Jun Kang
This network shows the impact of papers produced by Hee Jun Kang. 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 Hee Jun Kang. The network helps show where Hee Jun Kang may publish in the future.
Co-authors
The 25 scholars most cited alongside Hee Jun Kang, 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 48 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 96 | |
| 2 | 2012 | 61 | |
| 3 | 2000 | 58 | |
| 4 | 2021 | 40 | |
| 5 | 2003 | 33 | |
| 6 | 2004 | 33 | |
| 7 | 2015 | 29 | |
| 8 | 2021 | 21 | |
| 9 | 2018 | 16 | |
| 10 | 2003 | 16 | |
| 11 | 2022 | 15 | |
| 12 | 2015 | 11 | |
| 13 | 2009 | 10 | |
| 14 | 2023 | 10 | |
| 15 | 2024 | 9 | |
| 16 | 2021 | 9 | |
| 17 | 2013 | 9 | |
| 18 | 2023 | 8 | |
| 19 | 2024 | 7 | |
| 20 | 2023 | 7 |
About Hee Jun Kang
Hee Jun Kang is a scholar working on Artificial Intelligence, Cardiology and Cardiovascular Medicine, Surgery, Molecular Biology and Computer Vision and Pattern Recognition, having authored 48 papers that have together received 555 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (8 papers), Cardiac Imaging and Diagnostics (5 papers), Advanced X-ray and CT Imaging (4 papers), Artificial Intelligence in Healthcare (4 papers), Heat Transfer and Optimization (3 papers), Chaos control and synchronization (3 papers), Lipoproteins and Cardiovascular Health (3 papers) and Robotic Mechanisms and Dynamics (2 papers). The work is most often cited by research in Health Informatics (30 citations), Otorhinolaryngology (34 citations), Radiology, Nuclear Medicine and Imaging (150 citations), Health Information Management (27 citations) and Mechanical Engineering (102 citations). Hee Jun Kang has collaborated with scholars based in South Korea, United States and China. Frequent co-authors include Cheng-Xian Lin, M. A. Ebadian, Young‐Hak Kim, Dong Hyun Yang, Duy-Tang Hoang, June‐Goo Lee, Tae Joon Jun, Junsang Moon, Younghye Moon and Hsien‐Ming Lee. Their work appears in journals such as Scientific Reports, BMC Medical Informatics and Decision Making, Journal of Korean Medical Science, Nonlinear Dynamics and International Journal of Cardiology.
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.