Haoyuan Chen
- Artificial Intelligence top 2%
- Radiology, Nuclear Medicine and Imaging top 5%
- Computer Vision and Pattern Recognition top 5%
- Oncology
- Biomedical Engineering
- Co-authors
- Marcin GrzegorzekChen LiHongzan SunWeiming HuMd Mamunur RahamanWanli LiuChanghao SunXiaoyan Li
- Topics
- AI in cancer detection (13 papers)Radiomics and Machine Learning in Medical Imaging (10 papers)Colorectal Cancer Screening and Detection (5 papers)
- Journals
- SHILAP Revista de lepidopterologíaPattern RecognitionArtificial Intelligence Review
- Partner nations
- ChinaGermanyUnited States
In The Last Decade
Haoyuan Chen
24 papers receiving 803 citations
Hit Papers
Peers
Comparison fields: 5 of 102
- Artificial Intelligence 506
- Radiology, Nuclear Medicine and Imaging 327
- Computer Vision and Pattern Recognition 253
- Oncology 110
- Biomedical Engineering 78
Countries citing papers authored by Haoyuan Chen
This map shows the geographic impact of Haoyuan Chen'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 Haoyuan Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Haoyuan Chen more than expected).
Fields of papers citing papers by Haoyuan Chen
This network shows the impact of papers produced by Haoyuan Chen. 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 Haoyuan Chen. The network helps show where Haoyuan Chen may publish in the future.
Co-authorship network of co-authors of Haoyuan Chen
This figure shows the co-authorship network connecting the top 25 collaborators of Haoyuan Chen. A scholar is included among the top collaborators of Haoyuan Chen 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 Haoyuan Chen. Haoyuan Chen 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 | 1 | |
| 3 | 2 | |
| 4 | 0 | |
| 5 | 15 | |
| 6 | 38 | |
| 7 | 16 | |
| 8 | 3 | |
| 9 | 1 | |
| 10 | 22 | |
| 11 | 3 | |
| 12 | 5 | |
| 13 | 67 | |
| 14 | 101 | |
| 15 | 15 | |
| 16 | 49 | |
| 17 | 1 | |
| 18 | 54 | |
| 19 | 16 | |
| 20 | 1 |
About Haoyuan Chen
Haoyuan Chen is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition, having authored 25 papers that have together received 813 indexed citations. Recurring topics across this work include AI in cancer detection (13 papers), Radiomics and Machine Learning in Medical Imaging (10 papers) and Colorectal Cancer Screening and Detection (5 papers). The work is most often cited by research in Artificial Intelligence (506 citations), Radiology, Nuclear Medicine and Imaging (327 citations) and Health Informatics (17 citations). Haoyuan Chen has collaborated with scholars based in China, Germany and United States. Frequent co-authors include Marcin Grzegorzek, Chen Li, Hongzan Sun, Weiming Hu, Md Mamunur Rahaman, Wanli Liu, Changhao Sun, Xiaoyan Li, Yudong Yao and Yixin Li. Their work appears in journals such as SHILAP Revista de lepidopterología, Pattern Recognition and Artificial Intelligence Review.
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.