Weiwei Zong
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 5%
- Electrical and Electronic Engineering
- Control and Systems Engineering top 10%
- Radiology, Nuclear Medicine and Imaging
- Topics
- Machine Learning and ELM (7 papers)Radiomics and Machine Learning in Medical Imaging (6 papers)Prostate Cancer Diagnosis and Treatment (4 papers)
- Cited by
- Artificial IntelligenceComputer Vision and Pattern RecognitionHealth Information Management
- Journals
- Cancer ResearchScientific ReportsInternational Journal of Radiation Oncology*Biology*Physics
- Partner nations
- United StatesChinaSingapore
In The Last Decade
Weiwei Zong
17 papers receiving 875 citations
Hit Papers
Peers
Comparison fields: 5 of 100
- Artificial Intelligence 726
- Computer Vision and Pattern Recognition 244
- Electrical and Electronic Engineering 168
- Control and Systems Engineering 79
- Radiology, Nuclear Medicine and Imaging 62
Countries citing papers authored by Weiwei Zong
This map shows the geographic impact of Weiwei Zong'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 Weiwei Zong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weiwei Zong more than expected).
Fields of papers citing papers by Weiwei Zong
This network shows the impact of papers produced by Weiwei Zong. 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 Weiwei Zong. The network helps show where Weiwei Zong may publish in the future.
Co-authorship network of co-authors of Weiwei Zong
This figure shows the co-authorship network connecting the top 25 collaborators of Weiwei Zong. A scholar is included among the top collaborators of Weiwei Zong 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 Weiwei Zong. Weiwei Zong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 6 | |
| 3 | 4 | |
| 4 | 36 | |
| 5 | 1 | |
| 6 | 15 | |
| 7 | 1 | |
| 8 | 2 | |
| 9 | 1 | |
| 10 | 9 | |
| 11 | 2 | |
| 12 | 31 | |
| 13 | 4 | |
| 14 | 61 | |
| 15 | Weighted extreme learning machine for imbalance learningbreakdown → | 568 |
| 16 | 1 | |
| 17 | 161 |
About Weiwei Zong
Weiwei Zong is a scholar working on Neurology, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging, having authored 17 papers that have together received 906 indexed citations. Recurring topics across this work include Machine Learning and ELM (7 papers), Radiomics and Machine Learning in Medical Imaging (6 papers) and Prostate Cancer Diagnosis and Treatment (4 papers). The work is most often cited by research in Artificial Intelligence (726 citations), Computer Vision and Pattern Recognition (244 citations) and Health Information Management (16 citations). Weiwei Zong has collaborated with scholars based in United States, China and Singapore. Frequent co-authors include Guang-Bin Huang, Yiqiang Chen, Weimin Huang, Ning Li, Zhiping Lin, Yuping Duan, Jiayin Zhou, Ning Wen, Milan Pantelic and Mohamed A. Elshaikh. Their work appears in journals such as Cancer Research, Scientific Reports and International Journal of Radiation Oncology*Biology*Physics.
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.