Synho Do
- Health Informatics top 0.05%
- Artificial Intelligence in Healthcare and Education 8
-
- Medical Imaging Techniques and Applications 31
- Radiation Dose and Imaging 22
- Radiomics and Machine Learning in Medical Imaging 16
- Cardiac Imaging and Diagnostics 8
- COVID-19 diagnosis using AI 5
- Biomedical Engineering top 2%
- Advanced X-ray and CT Imaging 34
- Oral Surgery top 2%
- Artificial Intelligence top 2%
- AI in cancer detection 8
- Co-authors
- Mannudeep K. KalraHyunkwang LeeJames A. BrinkKeith J. DreyerHomer PienShahein TajmirGarry ChoySarabjeet Singh
- Journals
- Journal of Computer Assisted Tomography (6 papers)Radiology (5 papers)Journal of Digital Imaging (4 papers)
- Partner nations
- United StatesSouth KoreaGermany
In The Last Decade
Synho Do
69 papers receiving 3.8k citations
Hit Papers
Peers
Comparison fields: 5 of 162
- Health Informatics 664
- Radiology, Nuclear Medicine and Imaging 2.5k
- Biomedical Engineering 1.5k
- Oral Surgery 215
- Artificial Intelligence 622
Countries citing papers authored by Synho Do
This map shows the geographic impact of Synho Do'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 Synho Do with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Synho Do more than expected).
Fields of papers citing papers by Synho Do
This network shows the impact of papers produced by Synho Do. 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 Synho Do. The network helps show where Synho Do may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Synho Do, 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 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 1 | |
| 6 | 2023 | 9 | |
| 7 | 2022 | 52 | |
| 8 | 2019 | 33 | |
| 9 | 2018 | 89 | |
| 10 | 2018 | 30 | |
| 11 | 2018 | 64 | |
| 12 | 2018 | 13 | |
| 13 | Medical Image Deep Learning with Hospital PACS Dataset. | 2015 | 13 |
| 14 | 2015 | 11 | |
| 15 | 2013 | 28 | |
| 16 | 2013 | 58 | |
| 17 | 2013 | 14 | |
| 18 | 2011 | 104 | |
| 19 | 2010 | 25 | |
| 20 | 2006 | 9 |
About Synho Do
Synho Do is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging, Biomedical Engineering, Artificial Intelligence and Radiation, having authored 74 papers that have together received 3.8k indexed citations. Recurring topics across this work include Advanced X-ray and CT Imaging (34 papers), Medical Imaging Techniques and Applications (31 papers), Radiation Dose and Imaging (22 papers), Radiomics and Machine Learning in Medical Imaging (16 papers), Cardiac Imaging and Diagnostics (8 papers), AI in cancer detection (8 papers), Artificial Intelligence in Healthcare and Education (8 papers) and COVID-19 diagnosis using AI (5 papers). The work is most often cited by research in Health Informatics (664 citations), Radiology, Nuclear Medicine and Imaging (2.5k citations), Biomedical Engineering (1.5k citations), Oral Surgery (215 citations) and Artificial Intelligence (622 citations). Synho Do has collaborated with scholars based in United States, South Korea and Germany. Frequent co-authors include Mannudeep K. Kalra, Hyunkwang Lee, James A. Brink, Keith J. Dreyer, Homer Pien, Shahein Tajmir, Garry Choy, Sarabjeet Singh, Michael A. Blake and Jiang Hsieh. Their work appears in journals such as Journal of Computer Assisted Tomography, Radiology, Journal of Digital Imaging, American Journal of Roentgenology and IEEE Transactions on Medical Imaging.
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.