John Ryu
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
- Radiology practices and education
Papers in
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- Radiomics and Machine Learning in Medical Imaging 2
- Radiology practices and education 2
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- Cancer-related gene regulation 2
- Co-authors
- Luciano M. Prevedello (4 shared papers)Mutlu Demirer (2 shared papers)Barbaros S. Erdal (2 shared papers)Kevin J. Little (2 shared papers)Richard White (1 shared paper)Mina S. Makary (2 shared papers)Xuan V. Nguyen (2 shared papers)Kelvin Wong (1 shared paper)
- Journals
- Journal of Digital Imaging (1 paper)Radiology (1 paper)Journal of Vascular Surgery Venous and Lymphatic Disorders (1 paper)American Journal of Neuroradiology (1 paper)Cancer Research (1 paper)
- Partner nations
- United StatesItaly
In The Last Decade
John Ryu
7 papers receiving 208 citations
Peers
Comparison fields: 5 of 57
- Health Informatics 59
- Radiology, Nuclear Medicine and Imaging 111
- Internal Medicine 14
- Neurology 45
- Neurology 23
Countries citing papers authored by John Ryu
This map shows the geographic impact of John Ryu'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 John Ryu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Ryu more than expected).
Fields of papers citing papers by John Ryu
This network shows the impact of papers produced by John Ryu. 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 John Ryu. The network helps show where John Ryu may publish in the future.
Co-authors
The 25 scholars most cited alongside John Ryu, 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 | 2017 | 180 | |
| 2 | 2017 | 9 | |
| 3 | 2022 | 9 | |
| 4 | 2017 | 7 | |
| 5 | 2022 | 4 | |
| 6 | 2011 | 2 | |
| 7 | 2010 | 1 | |
| 8 | 2019 | 1 |
About John Ryu
John Ryu is a scholar working on Radiology, Nuclear Medicine and Imaging, Molecular Biology, Health Informatics, Biomedical Engineering and Cardiology and Cardiovascular Medicine, having authored 8 papers that have together received 213 indexed citations. Recurring topics across this work include Cancer-related gene regulation (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Artificial Intelligence in Healthcare and Education (2 papers), Radiology practices and education (2 papers), Advanced X-ray and CT Imaging (2 papers), Brain Metastases and Treatment (1 paper), Education and Learning Interventions (1 paper) and Health and Wellbeing Research (1 paper). The work is most often cited by research in Health Informatics (59 citations), Radiology, Nuclear Medicine and Imaging (111 citations), Internal Medicine (14 citations), Neurology (45 citations) and Neurology (23 citations). John Ryu has collaborated with scholars based in United States and Italy. Frequent co-authors include Luciano M. Prevedello, Mutlu Demirer, Barbaros S. Erdal, Kevin J. Little, Richard White, Mina S. Makary, Xuan V. Nguyen, Kelvin Wong, Xueliang Pan and Engin Dikici. Their work appears in journals such as Journal of Digital Imaging, Radiology, Journal of Vascular Surgery Venous and Lymphatic Disorders, American Journal of Neuroradiology and Cancer Research.
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.