Weijie Chen
- Radiology, Nuclear Medicine and Imaging top 1%
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 2%
- Pulmonary and Respiratory Medicine
- Oncology
- Co-authors
- Maryellen L. GigerUlrich BickNicholas PetrickGillian M. NewsteadBrandon D. GallasLe KangHui LiShiliang Pu
- Topics
- Radiomics and Machine Learning in Medical Imaging (20 papers)AI in cancer detection (19 papers)Domain Adaptation and Few-Shot Learning (18 papers)
- Partner nations
- United StatesChinaGermany
In The Last Decade
Weijie Chen
67 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 135
- Radiology, Nuclear Medicine and Imaging 935
- Artificial Intelligence 805
- Computer Vision and Pattern Recognition 495
- Pulmonary and Respiratory Medicine 178
- Oncology 123
Countries citing papers authored by Weijie Chen
This map shows the geographic impact of Weijie 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 Weijie Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weijie Chen more than expected).
Fields of papers citing papers by Weijie Chen
This network shows the impact of papers produced by Weijie 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 Weijie Chen. The network helps show where Weijie Chen may publish in the future.
Co-authorship network of co-authors of Weijie Chen
This figure shows the co-authorship network connecting the top 25 collaborators of Weijie Chen. A scholar is included among the top collaborators of Weijie 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 Weijie Chen. Weijie 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 | 6 | |
| 2 | 8 | |
| 3 | 8 | |
| 4 | 1 | |
| 5 | 5 | |
| 6 | 77 | |
| 7 | 16 | |
| 8 | 0 | |
| 9 | 3 | |
| 10 | 5 | |
| 11 | 3 | |
| 12 | 36 | |
| 13 | 1 | |
| 14 | 0 | |
| 15 | 38 | |
| 16 | 0 | |
| 17 | 274 | |
| 18 | Bayesian Inference for Double Generalized Linear Regression Models of the Inverse Gaussian Distribution | 0 |
| 19 | 10 | |
| 20 | 155 |
About Weijie Chen
Weijie Chen is a scholar working on Artificial Intelligence, Health Informatics and Computer Vision and Pattern Recognition, having authored 75 papers that have together received 1.9k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (20 papers), AI in cancer detection (19 papers) and Domain Adaptation and Few-Shot Learning (18 papers). The work is most often cited by research in Health Informatics (71 citations), Radiology, Nuclear Medicine and Imaging (935 citations) and Artificial Intelligence (805 citations). Weijie Chen has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Maryellen L. Giger, Ulrich Bick, Nicholas Petrick, Gillian M. Newstead, Brandon D. Gallas, Le Kang, Hui Li, Shiliang Pu, Lan Li and Berkman Sahiner. Their work appears in journals such as PLoS ONE, IEEE Transactions on Image Processing and Magnetic Resonance in Medicine.
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.