Sehyo Yune
Impact in
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
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- Sepsis Diagnosis and Treatment 2
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- Vasculitis and related conditions 3
- Lung Cancer Diagnosis and Treatment 2
- Co-authors
- Synho Do (6 shared papers)Myeongchan Kim (5 shared papers)Shahein Tajmir (4 shared papers)Hyunkwang Lee (4 shared papers)Javier M. Romero (1 shared paper)Ramón González (1 shared paper)Stuart R. Pomerantz (1 shared paper)Mohammad Mansouri (1 shared paper)
- Journals
- Allergy Asthma and Immunology Research (3 papers)Scientific Reports (2 papers)Journal of Korean Medical Science (2 papers)Journal of Digital Imaging (1 paper)JMIR mhealth and uhealth (1 paper)
- Partner nations
- South KoreaUnited StatesGermany
In The Last Decade
Sehyo Yune
22 papers receiving 758 citations
Sehyo Yune's Hit Papers
Peers
Comparison fields: 5 of 116
- Health Informatics 162
- Radiology, Nuclear Medicine and Imaging 343
- Neurology 57
- Neurology 94
- Artificial Intelligence 181
Countries citing papers authored by Sehyo Yune
This map shows the geographic impact of Sehyo Yune'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 Sehyo Yune with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sehyo Yune more than expected).
Fields of papers citing papers by Sehyo Yune
This network shows the impact of papers produced by Sehyo Yune. 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 Sehyo Yune. The network helps show where Sehyo Yune may publish in the future.
Co-authors
The 25 scholars most cited alongside Sehyo Yune, 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 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | An explainable deep-learning algorithm for the detection of acute intracranial haemorrhage from small datasets Hit paper breakdown → | 2018 | 309 |
| 2 | 2019 | 169 | |
| 3 | 2018 | 89 | |
| 4 | 2019 | 33 | |
| 5 | 2018 | 30 | |
| 6 | 2016 | 23 | |
| 7 | 2015 | 22 | |
| 8 | 2017 | 19 | |
| 9 | 2019 | 13 | |
| 10 | 2016 | 13 | |
| 11 | 2022 | 10 | |
| 12 | 2014 | 10 | |
| 13 | 2015 | 9 | |
| 14 | 2014 | 7 | |
| 15 | 2013 | 5 | |
| 16 | Hepatitis B virus reactivation during anti-cancer chemotherapy in patients with past hepatitis B virus infection. | 2014 | 4 |
| 17 | 2013 | 4 | |
| 18 | 2022 | 4 | |
| 19 | 2017 | 2 | |
| 20 | 2013 | 1 |
About Sehyo Yune
Sehyo Yune is a scholar working on Epidemiology, Pulmonary and Respiratory Medicine, Rheumatology, Radiology, Nuclear Medicine and Imaging and Infectious Diseases, having authored 22 papers that have together received 778 indexed citations. Recurring topics across this work include Vasculitis and related conditions (3 papers), Eosinophilic Disorders and Syndromes (3 papers), COVID-19 diagnosis using AI (2 papers), Urticaria and Related Conditions (2 papers), Lung Cancer Diagnosis and Treatment (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Sepsis Diagnosis and Treatment (2 papers) and Soft tissue tumor case studies (1 paper). The work is most often cited by research in Health Informatics (162 citations), Radiology, Nuclear Medicine and Imaging (343 citations), Neurology (57 citations), Neurology (94 citations) and Artificial Intelligence (181 citations). Sehyo Yune has collaborated with scholars based in South Korea, United States and Germany. Frequent co-authors include Synho Do, Myeongchan Kim, Shahein Tajmir, Hyunkwang Lee, Javier M. Romero, Ramón González, Stuart R. Pomerantz, Mohammad Mansouri, Shahmir Kamalian and Michael H. Lev. Their work appears in journals such as Allergy Asthma and Immunology Research, Scientific Reports, Journal of Korean Medical Science, Journal of Digital Imaging and JMIR mhealth and uhealth.
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.