Sangwon Shin
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
Papers in
- Oncology 7
- Colorectal Cancer Treatments and Studies 3
- HER2/EGFR in Cancer Research 2
- Lung Cancer Research Studies 2
- Colorectal Cancer Surgical Treatments 1
-
- Lung Cancer Treatments and Mutations 2
- Gastric Cancer Management and Outcomes 2
- Co-authors
- Soo Ick Cho (6 shared papers)Jong Seok Ahn (1 shared paper)Seokhwi Kim (1 shared paper)Eun Kyung Park (1 shared paper)Su‐A Yang (1 shared paper)Ki Hwan Kim (1 shared paper)Chan‐Young Ock (6 shared papers)Jung Hun Kang (1 shared paper)
- Journals
- Journal of Clinical Oncology (5 papers)JCO Precision Oncology (1 paper)BMC Cancer (1 paper)Cancer Medicine (1 paper)Breast Cancer Research (1 paper)
- Partner nations
- South KoreaUnited StatesJapan
In The Last Decade
Sangwon Shin
12 papers receiving 128 citations
Peers
Comparison fields: 5 of 41
- Health Informatics 18
- Radiology, Nuclear Medicine and Imaging 42
- Oncology 49
- Artificial Intelligence 50
- Cancer Research 17
Countries citing papers authored by Sangwon Shin
This map shows the geographic impact of Sangwon Shin'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 Sangwon Shin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sangwon Shin more than expected).
Fields of papers citing papers by Sangwon Shin
This network shows the impact of papers produced by Sangwon Shin. 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 Sangwon Shin. The network helps show where Sangwon Shin may publish in the future.
Co-authors
The 25 scholars most cited alongside Sangwon Shin, 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 | 2023 | 76 | |
| 2 | 2008 | 18 | |
| 3 | 2024 | 14 | |
| 4 | Obesity from the viewpoint of metabolic rate | 2003 | 5 |
| 5 | 2024 | 3 | |
| 6 | 2024 | 3 | |
| 7 | A phase II study of S-1 monotherapy administered for 2 weeks of a 3-week cycle in advanced gastric cancer patients with poor performance status | 2007 | 3 |
| 8 | 2008 | 3 | |
| 9 | 2025 | 2 | |
| 10 | 2025 | 2 | |
| 11 | 2024 | 2 | |
| 12 | 2023 | 1 | |
| 13 | 2024 | 0 | |
| 14 | 2024 | 0 | |
| 15 | 2024 | 0 | |
| 16 | 2025 | 0 |
About Sangwon Shin
Sangwon Shin is a scholar working on Oncology, Pulmonary and Respiratory Medicine, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Surgery, having authored 16 papers that have together received 132 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (6 papers), AI in cancer detection (4 papers), Colorectal Cancer Treatments and Studies (3 papers), Lung Cancer Treatments and Mutations (2 papers), HER2/EGFR in Cancer Research (2 papers), Lung Cancer Research Studies (2 papers), Gastric Cancer Management and Outcomes (2 papers) and Colorectal Cancer Surgical Treatments (1 paper). The work is most often cited by research in Health Informatics (18 citations), Radiology, Nuclear Medicine and Imaging (42 citations), Oncology (49 citations), Artificial Intelligence (50 citations) and Cancer Research (17 citations). Sangwon Shin has collaborated with scholars based in South Korea, United States and Japan. Frequent co-authors include Soo Ick Cho, Jong Seok Ahn, Seokhwi Kim, Eun Kyung Park, Su‐A Yang, Ki Hwan Kim, Chan‐Young Ock, Jung Hun Kang, Chang‐Ok Suh and Sujin Kim. Their work appears in journals such as Journal of Clinical Oncology, JCO Precision Oncology, BMC Cancer, Cancer Medicine and Breast 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.