Yoon‐Chul Kim
Impact in
- Signal Processing top 5%
- Speech and Audio Processing
-
- Advanced MRI Techniques and Applications
- Advanced Neuroimaging Techniques and Applications
Papers in
-
- Advanced MRI Techniques and Applications 20
- Cardiac Imaging and Diagnostics 12
- Medical Imaging Techniques and Applications 5
- Co-authors
- Krishna S. NayakShrikanth NarayananDani ByrdErik BreschYinghua ZhuMichael ProctorAsterios ToutiosMichael C. K. Khoo
- Journals
- Magnetic Resonance in Medicine (6 papers)Scientific Reports (2 papers)Journal of Stroke (2 papers)Physica Medica (2 papers)Tomography (2 papers)
- Partner nations
- South KoreaUnited StatesAustralia
In The Last Decade
Yoon‐Chul Kim
68 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 133
- Signal Processing 197
- Radiology, Nuclear Medicine and Imaging 387
- Experimental and Cognitive Psychology 153
- Physiology 190
- Artificial Intelligence 212
Countries citing papers authored by Yoon‐Chul Kim
This map shows the geographic impact of Yoon‐Chul Kim'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 Yoon‐Chul Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yoon‐Chul Kim more than expected).
Fields of papers citing papers by Yoon‐Chul Kim
This network shows the impact of papers produced by Yoon‐Chul Kim. 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 Yoon‐Chul Kim. The network helps show where Yoon‐Chul Kim may publish in the future.
Co-authors
The 25 scholars most cited alongside Yoon‐Chul Kim, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2023 | 4 | |
| 3 | 2023 | 7 | |
| 4 | 2023 | 3 | |
| 5 | 2023 | 1 | |
| 6 | 2023 | 1 | |
| 7 | 2022 | 2 | |
| 8 | 2022 | 10 | |
| 9 | 2021 | 4 | |
| 10 | 2021 | 15 | |
| 11 | 2019 | 17 | |
| 12 | 2019 | 13 | |
| 13 | 2018 | 17 | |
| 14 | 2018 | 6 | |
| 15 | 2017 | 7 | |
| 16 | 2016 | 4 | |
| 17 | 2011 | 27 | |
| 18 | 2010 | 17 | |
| 19 | 2010 | 42 | |
| 20 | The role of microstructure of automotive gray iron disks in hot spot formation | 2006 | 0 |
About Yoon‐Chul Kim
Yoon‐Chul Kim is a scholar working on Radiology, Nuclear Medicine and Imaging, Transplantation, Signal Processing, Pulmonary and Respiratory Medicine and Neurology, having authored 71 papers that have together received 1.3k indexed citations. Recurring topics across this work include Advanced MRI Techniques and Applications (20 papers), Cardiac Imaging and Diagnostics (12 papers), Cerebrovascular and Carotid Artery Diseases (11 papers), Acute Ischemic Stroke Management (9 papers), Speech and Audio Processing (6 papers), Voice and Speech Disorders (6 papers), Medical Imaging Techniques and Applications (5 papers) and Cardiovascular Function and Risk Factors (5 papers). The work is most often cited by research in Signal Processing (197 citations), Radiology, Nuclear Medicine and Imaging (387 citations), Experimental and Cognitive Psychology (153 citations), Physiology (190 citations) and Artificial Intelligence (212 citations). Yoon‐Chul Kim has collaborated with scholars based in South Korea, United States and Australia. Frequent co-authors include Krishna S. Nayak, Shrikanth Narayanan, Dani Byrd, Erik Bresch, Yinghua Zhu, Michael Proctor, Asterios Toutios, Michael C. K. Khoo, Dong Hwan Sohn and Yeon Hyeon Choe. Their work appears in journals such as Magnetic Resonance in Medicine, Scientific Reports, Journal of Stroke, Physica Medica and Tomography.
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.