Hyunsuk Shim
- Cancer Research top 0.5%
- Cancer, Hypoxia, and Metabolism 11
- Oncology top 1%
- Chemokine receptors and signaling 25
- Cytokine Signaling Pathways and Interactions 8
- Molecular Biology top 2%
- Immunology top 2%
- Immunotherapy and Immune Responses 17
- Genetics top 2%
- Glioma Diagnosis and Treatment 32
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- Medical Imaging Techniques and Applications 36
- Advanced MRI Techniques and Applications 22
- Radiomics and Machine Learning in Medical Imaging 20
- Co-authors
- Zhongxing LiangChi V. DangYounghyoun YoonBrian C. LewisAizhi ZhuChristine DoldeRiccardo Dalla‐FaveraRichard A. Jungmann
- Journals
- Proceedings of the National Academy of Sciences (2 papers)Journal of Biological Chemistry (3 papers)Journal of Clinical Oncology (2 papers)
- Partner nations
- United StatesChinaSouth Korea
In The Last Decade
Hyunsuk Shim
124 papers receiving 6.9k citations
Hit Papers
Peers
Comparison fields: 5 of 137
- Cancer Research 2.2k
- Oncology 2.1k
- Molecular Biology 3.8k
- Immunology 1.2k
- Genetics 558
Countries citing papers authored by Hyunsuk Shim
This map shows the geographic impact of Hyunsuk Shim'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 Hyunsuk Shim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hyunsuk Shim more than expected).
Fields of papers citing papers by Hyunsuk Shim
This network shows the impact of papers produced by Hyunsuk Shim. 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 Hyunsuk Shim. The network helps show where Hyunsuk Shim may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Hyunsuk Shim, 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 | 0 | |
| 2 | 2024 | 1 | |
| 3 | 2023 | 3 | |
| 4 | 2023 | 1 | |
| 5 | 2023 | 2 | |
| 6 | 2023 | 9 | |
| 7 | 2019 | 8 | |
| 8 | 2019 | 31 | |
| 9 | 2018 | 26 | |
| 10 | High-resolution CT Image Retrieval Using Sparse Convolutional Neural Network | 2018 | 1 |
| 11 | 2018 | 40 | |
| 12 | 2018 | 12 | |
| 13 | 2016 | 20 | |
| 14 | 2016 | 19 | |
| 15 | 2014 | 13 | |
| 16 | 2010 | 56 | |
| 17 | 2009 | 98 | |
| 18 | MSX-122, an orally available small molecule targeting CXCR4, inhibits primary tumor growth in an orthotopic mouse model of lung cancer and improves the effect of paclitaxel | 2008 | 3 |
| 19 | 2008 | 17 | |
| 20 | 2007 | 100 |
About Hyunsuk Shim
Hyunsuk Shim is a scholar working on Genetics, Radiology, Nuclear Medicine and Imaging and Oncology, having authored 126 papers that have together received 7.0k indexed citations. Recurring topics across this work include Medical Imaging Techniques and Applications (36 papers), Glioma Diagnosis and Treatment (32 papers), Chemokine receptors and signaling (25 papers), Advanced MRI Techniques and Applications (22 papers), Radiomics and Machine Learning in Medical Imaging (20 papers), Immunotherapy and Immune Responses (17 papers), Cancer, Hypoxia, and Metabolism (11 papers) and Cytokine Signaling Pathways and Interactions (8 papers). The work is most often cited by research in Cancer Research (2.2k citations), Oncology (2.1k citations) and Molecular Biology (3.8k citations). Hyunsuk Shim has collaborated with scholars based in United States, China and South Korea. Frequent co-authors include Zhongxing Liang, Chi V. Dang, Younghyoun Yoon, Brian C. Lewis, Aizhi Zhu, Christine Dolde, Riccardo Dalla‐Favera, Richard A. Jungmann, Daniel Lee and C. Chris Yun. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Oncology.
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.