Yuankai Huo
- Radiology, Nuclear Medicine and Imaging top 1%
- Computer Vision and Pattern Recognition top 1%
- Artificial Intelligence top 2%
- Cognitive Neuroscience top 5%
- Biomedical Engineering top 10%
- Co-authors
- Bennett A. LandmanShunxing BaoSusan M. ResnickZhoubing XuRichard G. AbramsonRuining DengAndrew J. PlassardYudong Zhang
- Topics
- Medical Image Segmentation Techniques (37 papers)Radiomics and Machine Learning in Medical Imaging (37 papers)AI in cancer detection (34 papers)
- Cited by
- Health InformaticsRadiology, Nuclear Medicine and ImagingComputer Vision and Pattern Recognition
- Partner nations
- United StatesChinaCanada
In The Last Decade
Yuankai Huo
168 papers receiving 2.6k citations
Hit Papers
Peers
Comparison fields: 5 of 160
- Radiology, Nuclear Medicine and Imaging 1.1k
- Computer Vision and Pattern Recognition 729
- Artificial Intelligence 613
- Cognitive Neuroscience 376
- Biomedical Engineering 290
Countries citing papers authored by Yuankai Huo
This map shows the geographic impact of Yuankai Huo'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 Yuankai Huo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuankai Huo more than expected).
Fields of papers citing papers by Yuankai Huo
This network shows the impact of papers produced by Yuankai Huo. 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 Yuankai Huo. The network helps show where Yuankai Huo may publish in the future.
Co-authorship network of co-authors of Yuankai Huo
This figure shows the co-authorship network connecting the top 25 collaborators of Yuankai Huo. A scholar is included among the top collaborators of Yuankai Huo 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 Yuankai Huo. Yuankai Huo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | Multichannel meta-imagers for accelerating machine visionbreakdown → | 69 |
| 6 | 5 | |
| 7 | 0 | |
| 8 | 33 | |
| 9 | 24 | |
| 10 | 11 | |
| 11 | 5 | |
| 12 | 1 | |
| 13 | 4 | |
| 14 | 5 | |
| 15 | 7 | |
| 16 | 11 | |
| 17 | 36 | |
| 18 | 11 | |
| 19 | 112 | |
| 20 | 28 |
About Yuankai Huo
Yuankai Huo is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Biophysics, having authored 183 papers that have together received 2.7k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (37 papers), Radiomics and Machine Learning in Medical Imaging (37 papers) and AI in cancer detection (34 papers). The work is most often cited by research in Health Informatics (69 citations), Radiology, Nuclear Medicine and Imaging (1.1k citations) and Computer Vision and Pattern Recognition (729 citations). Yuankai Huo has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Bennett A. Landman, Shunxing Bao, Susan M. Resnick, Zhoubing Xu, Richard G. Abramson, Ruining Deng, Andrew J. Plassard, Yudong Zhang, Lenan Wu and Camilo Bermudez. Their work appears in journals such as PLoS ONE, Nature Nanotechnology and NeuroImage.
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.