Xiaohua Qian
- Radiology, Nuclear Medicine and Imaging top 2%
- Molecular Biology
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Cancer Research top 10%
- Co-authors
- Vicki L. RothmanGeorge P. TuszynskiThomas J. WangChencheng ZhangRui GuoXiaozhu LinRoberto F. NicosiaJun Li
- Topics
- Radiomics and Machine Learning in Medical Imaging (22 papers)AI in cancer detection (15 papers)Pancreatic and Hepatic Oncology Research (14 papers)
- Cited by
- Radiology, Nuclear Medicine and ImagingCancer ResearchComputer Vision and Pattern Recognition
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Xiaohua Qian
77 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 133
- Radiology, Nuclear Medicine and Imaging 619
- Molecular Biology 383
- Artificial Intelligence 344
- Computer Vision and Pattern Recognition 343
- Cancer Research 279
Countries citing papers authored by Xiaohua Qian
This map shows the geographic impact of Xiaohua Qian'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 Xiaohua Qian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaohua Qian more than expected).
Fields of papers citing papers by Xiaohua Qian
This network shows the impact of papers produced by Xiaohua Qian. 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 Xiaohua Qian. The network helps show where Xiaohua Qian may publish in the future.
Co-authorship network of co-authors of Xiaohua Qian
This figure shows the co-authorship network connecting the top 25 collaborators of Xiaohua Qian. A scholar is included among the top collaborators of Xiaohua Qian 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 Xiaohua Qian. Xiaohua Qian is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 6 | |
| 3 | 3 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 1 | |
| 7 | 3 | |
| 8 | 4 | |
| 9 | 12 | |
| 10 | 15 | |
| 11 | 5 | |
| 12 | 25 | |
| 13 | 32 | |
| 14 | 11 | |
| 15 | 57 | |
| 16 | 27 | |
| 17 | 13 | |
| 18 | 6 | |
| 19 | 15 | |
| 20 | 45 |
About Xiaohua Qian
Xiaohua Qian is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Neurology, having authored 82 papers that have together received 1.7k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (22 papers), AI in cancer detection (15 papers) and Pancreatic and Hepatic Oncology Research (14 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (619 citations), Cancer Research (279 citations) and Computer Vision and Pattern Recognition (343 citations). Xiaohua Qian has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Vicki L. Rothman, George P. Tuszynski, Thomas J. Wang, Chencheng Zhang, Rui Guo, Xiaozhu Lin, Roberto F. Nicosia, Jun Li, Hua Tan and Xueyan Li. Their work appears in journals such as Nature Communications, IEEE Transactions on Image Processing and IEEE Access.
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.