Rushi Jiao
About
In The Last Decade
Rushi Jiao
4 papers receiving 309 citations
Hit Papers
Peers
Comparison fields: 5 of 74
- Computer Vision and Pattern Recognition 167
- Artificial Intelligence 116
- Radiology, Nuclear Medicine and Imaging 116
- Neurology 64
- Biomedical Engineering 56
Countries citing papers authored by Rushi Jiao
This map shows the geographic impact of Rushi Jiao'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 Rushi Jiao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rushi Jiao more than expected).
Fields of papers citing papers by Rushi Jiao
This network shows the impact of papers produced by Rushi Jiao. 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 Rushi Jiao. The network helps show where Rushi Jiao may publish in the future.
Co-authorship network of co-authors of Rushi Jiao
This figure shows the co-authorship network connecting the top 25 collaborators of Rushi Jiao. A scholar is included among the top collaborators of Rushi Jiao 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 Rushi Jiao. Rushi Jiao 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 | Segment anything model for medical image segmentation: Current applications and future directions breakdown → | 111 |
| 4 | Learning with limited annotations: A survey on deep semi-supervised learning for medical image segmentation breakdown → | 142 |
| 5 | 54 | |
| 6 | 6 |
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.