Youngbin Shin
Impact in
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
- Geriatrics and Gerontology top 5%
- Frailty in Older Adults
Papers in
- Physiology 10
- Nutrition and Health in Aging 10
- Body Composition Measurement Techniques 3
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- Frailty in Older Adults 3
- Co-authors
- Kyung Won Kim (23 shared papers)Dong Wook Kim (3 shared papers)Seong Ho Park (3 shared papers)Hye Young Jang (1 shared paper)Yu Sub Sung (13 shared papers)Jimi Huh (5 shared papers)In‐Seob Lee (4 shared papers)Koeun Lee (2 shared papers)
- Journals
- Korean Journal of Radiology (5 papers)ULTRASONOGRAPHY (1 paper)Surgical Oncology (1 paper)Scientific Reports (1 paper)Medicine (1 paper)
- Partner nations
- South KoreaBelarus
In The Last Decade
Youngbin Shin
30 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 106
- Health Informatics 176
- Geriatrics and Gerontology 85
- Radiology, Nuclear Medicine and Imaging 440
- Physiology 466
- Artificial Intelligence 210
Countries citing papers authored by Youngbin Shin
This map shows the geographic impact of Youngbin 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 Youngbin Shin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Youngbin Shin more than expected).
Fields of papers citing papers by Youngbin Shin
This network shows the impact of papers produced by Youngbin 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 Youngbin Shin. The network helps show where Youngbin Shin may publish in the future.
Co-authors
The 25 scholars most cited alongside Youngbin 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
Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 363 | |
| 2 | 2019 | 247 | |
| 3 | 2020 | 213 | |
| 4 | 2019 | 110 | |
| 5 | 2019 | 59 | |
| 6 | 2019 | 58 | |
| 7 | 2021 | 58 | |
| 8 | 2020 | 52 | |
| 9 | 2021 | 46 | |
| 10 | 2020 | 44 | |
| 11 | 2018 | 37 | |
| 12 | 2017 | 29 | |
| 13 | 2022 | 22 | |
| 14 | 2019 | 21 | |
| 15 | 2021 | 21 | |
| 16 | 2019 | 15 | |
| 17 | 2021 | 12 | |
| 18 | 2017 | 10 | |
| 19 | 2018 | 8 | |
| 20 | 2022 | 8 |
About Youngbin Shin
Youngbin Shin is a scholar working on Physiology, Geriatrics and Gerontology, Radiology, Nuclear Medicine and Imaging, Social Psychology and Control and Systems Engineering, having authored 30 papers that have together received 1.5k indexed citations. Recurring topics across this work include Nutrition and Health in Aging (10 papers), Robotics and Automated Systems (3 papers), Frailty in Older Adults (3 papers), Body Composition Measurement Techniques (3 papers), Social Robot Interaction and HRI (3 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), AI in Service Interactions (2 papers) and Cancer Immunotherapy and Biomarkers (2 papers). The work is most often cited by research in Health Informatics (176 citations), Geriatrics and Gerontology (85 citations), Radiology, Nuclear Medicine and Imaging (440 citations), Physiology (466 citations) and Artificial Intelligence (210 citations). Youngbin Shin has collaborated with scholars based in South Korea and Belarus. Frequent co-authors include Kyung Won Kim, Dong Wook Kim, Seong Ho Park, Hye Young Jang, Yu Sub Sung, Jimi Huh, In‐Seob Lee, Koeun Lee, Kwon‐Ha Yoon and Yousun Ko. Their work appears in journals such as Korean Journal of Radiology, ULTRASONOGRAPHY, Surgical Oncology, Scientific Reports and Medicine.
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.