Dong Wei
- Radiology, Nuclear Medicine and Imaging top 10%
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 5%
- Electrical and Electronic Engineering
- Neurology
- Topics
- Radiomics and Machine Learning in Medical Imaging (14 papers)COVID-19 diagnosis using AI (8 papers)Advanced Neural Network Applications (7 papers)
- Cited by
- Health InformaticsRadiology, Nuclear Medicine and ImagingComputer Vision and Pattern Recognition
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Biomedical EngineeringIEEE Transactions on Medical Imaging
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Dong Wei
34 papers receiving 411 citations
Peers
Comparison fields: 5 of 88
- Radiology, Nuclear Medicine and Imaging 205
- Artificial Intelligence 163
- Computer Vision and Pattern Recognition 146
- Electrical and Electronic Engineering 48
- Neurology 45
Countries citing papers authored by Dong Wei
This map shows the geographic impact of Dong Wei'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 Dong Wei with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dong Wei more than expected).
Fields of papers citing papers by Dong Wei
This network shows the impact of papers produced by Dong Wei. 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 Dong Wei. The network helps show where Dong Wei may publish in the future.
Co-authorship network of co-authors of Dong Wei
This figure shows the co-authorship network connecting the top 25 collaborators of Dong Wei. A scholar is included among the top collaborators of Dong Wei 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 Dong Wei. Dong Wei 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 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 3 | |
| 7 | 7 | |
| 8 | 6 | |
| 9 | 4 | |
| 10 | 24 | |
| 11 | 28 | |
| 12 | 2 | |
| 13 | An Evolutionary Study of Configuration Design and Implementation in Cloud Systems (with Replication Package) | 1 |
| 14 | 58 | |
| 15 | 2 | |
| 16 | 13 | |
| 17 | 22 | |
| 18 | Online Network-Wide Anomaly Detection Algorithm Based on Multivariate Incremental Component Analysis | 1 |
| 19 | Research on Influencing Factors of Medical Health Website Information Availability | 1 |
| 20 | 1 |
About Dong Wei
Dong Wei is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Health Informatics, having authored 40 papers that have together received 422 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (14 papers), COVID-19 diagnosis using AI (8 papers) and Advanced Neural Network Applications (7 papers). The work is most often cited by research in Health Informatics (18 citations), Radiology, Nuclear Medicine and Imaging (205 citations) and Computer Vision and Pattern Recognition (146 citations). Dong Wei has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Yefeng Zheng, Kai Ma, Donghuan Lu, Peng Li, Tianyi Qian, Liansheng Wang, Shuang Yu, Shi Gu, Cheng Bian and Chenglang Yuan. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Biomedical Engineering and IEEE Transactions on Medical Imaging.
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.