Shunxing Bao
- Radiology, Nuclear Medicine and Imaging top 5%
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 5%
- Biomedical Engineering
- Neurology top 10%
- Co-authors
- Bennett A. LandmanYuankai HuoZhoubing XuCamilo BermudezRichard G. AbramsonPrasanna ParvathaneniAlbert AssadYucheng Tang
- Topics
- Radiomics and Machine Learning in Medical Imaging (20 papers)Medical Image Segmentation Techniques (17 papers)AI in cancer detection (17 papers)
- Cited by
- Radiology, Nuclear Medicine and ImagingHealth InformaticsComputer Vision and Pattern Recognition
- Partner nations
- United StatesGermanyChina
In The Last Decade
Shunxing Bao
76 papers receiving 894 citations
Peers
Comparison fields: 5 of 104
- Radiology, Nuclear Medicine and Imaging 472
- Computer Vision and Pattern Recognition 359
- Artificial Intelligence 257
- Biomedical Engineering 138
- Neurology 86
Countries citing papers authored by Shunxing Bao
This map shows the geographic impact of Shunxing Bao'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 Shunxing Bao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shunxing Bao more than expected).
Fields of papers citing papers by Shunxing Bao
This network shows the impact of papers produced by Shunxing Bao. 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 Shunxing Bao. The network helps show where Shunxing Bao may publish in the future.
Co-authorship network of co-authors of Shunxing Bao
This figure shows the co-authorship network connecting the top 25 collaborators of Shunxing Bao. A scholar is included among the top collaborators of Shunxing Bao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Shunxing Bao. Shunxing Bao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 16 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 6 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 1 | |
| 11 | 3 | |
| 12 | 7 | |
| 13 | 1 | |
| 14 | 7 | |
| 15 | 18 | |
| 16 | 7 | |
| 17 | 12 | |
| 18 | 19 | |
| 19 | 8 | |
| 20 | 55 |
About Shunxing Bao
Shunxing Bao is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Biophysics, having authored 85 papers that have together received 908 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (20 papers), Medical Image Segmentation Techniques (17 papers) and AI in cancer detection (17 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (472 citations), Health Informatics (25 citations) and Computer Vision and Pattern Recognition (359 citations). Shunxing Bao has collaborated with scholars based in United States, Germany and China. Frequent co-authors include Bennett A. Landman, Yuankai Huo, Zhoubing Xu, Camilo Bermudez, Richard G. Abramson, Prasanna Parvathaneni, Albert Assad, Yucheng Tang, Susan M. Resnick and Laurie E. Cutting. Their work appears in journals such as PLoS ONE, NeuroImage 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.