Yuxing Tang
- Radiology, Nuclear Medicine and Imaging top 5%
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Pulmonary and Respiratory Medicine
- Information Systems top 10%
- Topics
- COVID-19 diagnosis using AI (12 papers)Radiomics and Machine Learning in Medical Imaging (10 papers)AI in cancer detection (9 papers)
- Cited by
- Health InformaticsRadiology, Nuclear Medicine and ImagingComputer Vision and Pattern Recognition
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceJournal of Materials Chemistry AEnvironmental Pollution
- Partner nations
- ChinaUnited StatesFrance
In The Last Decade
Yuxing Tang
33 papers receiving 820 citations
Peers
Comparison fields: 5 of 103
- Radiology, Nuclear Medicine and Imaging 437
- Artificial Intelligence 380
- Computer Vision and Pattern Recognition 269
- Pulmonary and Respiratory Medicine 133
- Information Systems 84
Countries citing papers authored by Yuxing Tang
This map shows the geographic impact of Yuxing Tang'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 Yuxing Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuxing Tang more than expected).
Fields of papers citing papers by Yuxing Tang
This network shows the impact of papers produced by Yuxing Tang. 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 Yuxing Tang. The network helps show where Yuxing Tang may publish in the future.
Co-authorship network of co-authors of Yuxing Tang
This figure shows the co-authorship network connecting the top 25 collaborators of Yuxing Tang. A scholar is included among the top collaborators of Yuxing Tang 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 Yuxing Tang. Yuxing Tang 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 | 1 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 5 | |
| 6 | 2 | |
| 7 | 5 | |
| 8 | 3 | |
| 9 | 24 | |
| 10 | 13 | |
| 11 | 44 | |
| 12 | 42 | |
| 13 | 39 | |
| 14 | 57 | |
| 15 | 146 | |
| 16 | 32 | |
| 17 | 50 | |
| 18 | 90 | |
| 19 | Accelerating Program Behavior Analysis with Dynamic Binary Translation | 1 |
| 20 | Accurate vulnerability estimation for cache hierarchy | 3 |
About Yuxing Tang
Yuxing Tang is a scholar working on Radiology, Nuclear Medicine and Imaging, Hardware and Architecture and Artificial Intelligence, having authored 38 papers that have together received 842 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (12 papers), Radiomics and Machine Learning in Medical Imaging (10 papers) and AI in cancer detection (9 papers). The work is most often cited by research in Health Informatics (62 citations), Radiology, Nuclear Medicine and Imaging (437 citations) and Computer Vision and Pattern Recognition (269 citations). Yuxing Tang has collaborated with scholars based in China, United States and France. Frequent co-authors include Ronald M. Summers, Youbao Tang, Jing Xiao, Zhiyong Lu, Yifan Peng, Simon Masnou, Ke Yan, Xiaofang Wang, Emmanuel Dellandréa and Yingying Zhu. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of Materials Chemistry A and Environmental Pollution.
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.