Jianrui Ding
- Artificial Intelligence top 5%
- Radiology, Nuclear Medicine and Imaging top 5%
- Computer Vision and Pattern Recognition top 5%
- Neurology top 10%
- Biomedical Engineering
- Topics
- AI in cancer detection (17 papers)Radiomics and Machine Learning in Medical Imaging (8 papers)Visual Attention and Saliency Detection (7 papers)
- Cited by
- Radiology, Nuclear Medicine and ImagingComputer Vision and Pattern RecognitionArtificial Intelligence
- Journals
- Journal of The Electrochemical SocietyIEEE Transactions on Image ProcessingInternational Journal of Radiation Oncology*Biology*Physics
- Partner nations
- ChinaUnited StatesIreland
In The Last Decade
Jianrui Ding
37 papers receiving 722 citations
Hit Papers
Peers
Comparison fields: 5 of 87
- Artificial Intelligence 447
- Radiology, Nuclear Medicine and Imaging 367
- Computer Vision and Pattern Recognition 292
- Neurology 101
- Biomedical Engineering 94
Countries citing papers authored by Jianrui Ding
This map shows the geographic impact of Jianrui Ding'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 Jianrui Ding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jianrui Ding more than expected).
Fields of papers citing papers by Jianrui Ding
This network shows the impact of papers produced by Jianrui Ding. 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 Jianrui Ding. The network helps show where Jianrui Ding may publish in the future.
Co-authorship network of co-authors of Jianrui Ding
This figure shows the co-authorship network connecting the top 25 collaborators of Jianrui Ding. A scholar is included among the top collaborators of Jianrui Ding 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 Jianrui Ding. Jianrui Ding 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 | 2 | |
| 4 | CMUNEXT: An Efficient Medical Image Segmentation Network Based on Large Kernel and Skip Fusionbreakdown → | 49 |
| 5 | 2 | |
| 6 | 53 | |
| 7 | 3 | |
| 8 | 6 | |
| 9 | 2 | |
| 10 | 4 | |
| 11 | 49 | |
| 12 | 3 | |
| 13 | 2 | |
| 14 | 3 | |
| 15 | 7 | |
| 16 | 33 | |
| 17 | 40 | |
| 18 | 90 | |
| 19 | 21 | |
| 20 | 8 |
About Jianrui Ding
Jianrui Ding is a scholar working on Computer Vision and Pattern Recognition, Health Informatics and Artificial Intelligence, having authored 39 papers that have together received 736 indexed citations. Recurring topics across this work include AI in cancer detection (17 papers), Radiomics and Machine Learning in Medical Imaging (8 papers) and Visual Attention and Saliency Detection (7 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (367 citations), Computer Vision and Pattern Recognition (292 citations) and Artificial Intelligence (447 citations). Jianrui Ding has collaborated with scholars based in China, United States and Ireland. Frequent co-authors include Yingtao Zhang, Min Xian, Heng-Da Cheng, Boyu Zhang, Fei Xu, He Cheng, Chunping Ning, Jianhua Huang, Lingtao Wang and Jianhua Huang. Their work appears in journals such as Journal of The Electrochemical Society, IEEE Transactions on Image Processing and International Journal of Radiation Oncology*Biology*Physics.
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.