Yeqin Shao
- Computer Vision and Pattern Recognition top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Biomedical Engineering
- Artificial Intelligence
- Pulmonary and Respiratory Medicine
- Co-authors
- Dinggang ShenYaozong GaoQian WangDong NieLei XiangHuan ZhangXuhua RenJun Lian
- Topics
- Advanced Neural Network Applications (11 papers)Medical Image Segmentation Techniques (9 papers)Radiomics and Machine Learning in Medical Imaging (8 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE AccessIEEE Transactions on Biomedical Engineering
- Partner nations
- ChinaUnited StatesSouth Korea
In The Last Decade
Yeqin Shao
32 papers receiving 448 citations
Peers
Comparison fields: 5 of 83
- Computer Vision and Pattern Recognition 204
- Radiology, Nuclear Medicine and Imaging 204
- Biomedical Engineering 163
- Artificial Intelligence 91
- Pulmonary and Respiratory Medicine 54
Countries citing papers authored by Yeqin Shao
This map shows the geographic impact of Yeqin Shao'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 Yeqin Shao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yeqin Shao more than expected).
Fields of papers citing papers by Yeqin Shao
This network shows the impact of papers produced by Yeqin Shao. 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 Yeqin Shao. The network helps show where Yeqin Shao may publish in the future.
Co-authorship network of co-authors of Yeqin Shao
This figure shows the co-authorship network connecting the top 25 collaborators of Yeqin Shao. A scholar is included among the top collaborators of Yeqin Shao 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 Yeqin Shao. Yeqin Shao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 0 | |
| 3 | 8 | |
| 4 | 1 | |
| 5 | 5 | |
| 6 | 0 | |
| 7 | 8 | |
| 8 | 1 | |
| 9 | 2 | |
| 10 | 4 | |
| 11 | 19 | |
| 12 | 6 | |
| 13 | 105 | |
| 14 | 19 | |
| 15 | 1 | |
| 16 | 1 | |
| 17 | 32 | |
| 18 | 17 | |
| 19 | 17 | |
| 20 | Improved Kerberos Single Sign-on Protocol | 1 |
About Yeqin Shao
Yeqin Shao is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging and Energy Engineering and Power Technology, having authored 38 papers that have together received 458 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (11 papers), Medical Image Segmentation Techniques (9 papers) and Radiomics and Machine Learning in Medical Imaging (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (204 citations), Radiology, Nuclear Medicine and Imaging (204 citations) and Radiation (48 citations). Yeqin Shao has collaborated with scholars based in China, United States and South Korea. Frequent co-authors include Dinggang Shen, Yaozong Gao, Qian Wang, Dong Nie, Lei Xiang, Huan Zhang, Xuhua Ren, Jun Lian, Xin Yang and Yanrong Guo. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and IEEE Transactions on Biomedical Engineering.
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.