Weicong Chen
Impact in
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- Tryptophan and brain disorders
Papers in
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- Domain Adaptation and Few-Shot Learning 3
- Topic Modeling 2
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- Advanced Neural Network Applications 2
- Advanced Image and Video Retrieval Techniques 2
- Co-authors
- Haitao Sun (8 shared papers)Xiaodan Zhong (6 shared papers)Chunyu He (5 shared papers)Xuemei Yang (6 shared papers)Xu Tan (2 shared papers)Jialing Sun (6 shared papers)Yan Zhao (2 shared papers)Jihong Zhu (3 shared papers)
- Journals
- Journal of Ethnopharmacology (3 papers)Frontiers in Pharmacology (2 papers)Theriogenology (1 paper)Phytotherapy Research (1 paper)Journal of Neurophysiology (1 paper)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Weicong Chen
26 papers receiving 260 citations
Peers
Comparison fields: 5 of 80
- Biological Psychiatry 18
- Behavioral Neuroscience 7
- Endocrine and Autonomic Systems 12
- Computer Vision and Pattern Recognition 38
- Hepatology 13
Countries citing papers authored by Weicong Chen
This map shows the geographic impact of Weicong 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 Weicong Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weicong Chen more than expected).
Fields of papers citing papers by Weicong Chen
This network shows the impact of papers produced by Weicong 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 Weicong Chen. The network helps show where Weicong Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Weicong Chen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 34 | |
| 2 | 2021 | 25 | |
| 3 | 2023 | 24 | |
| 4 | 2023 | 24 | |
| 5 | 2023 | 21 | |
| 6 | 2023 | 19 | |
| 7 | 2017 | 18 | |
| 8 | 2021 | 13 | |
| 9 | 2022 | 9 | |
| 10 | 2019 | 9 | |
| 11 | 2023 | 9 | |
| 12 | 2021 | 8 | |
| 13 | 2020 | 8 | |
| 14 | 2021 | 7 | |
| 15 | 2024 | 7 | |
| 16 | 2023 | 7 | |
| 17 | 2024 | 6 | |
| 18 | 2022 | 4 | |
| 19 | 2022 | 2 | |
| 20 | Improving Long-Tailed Classification from Instance Level | 2021 | 2 |
About Weicong Chen
Weicong Chen is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Epidemiology and Infectious Diseases, having authored 30 papers that have together received 263 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (3 papers), SARS-CoV-2 detection and testing (3 papers), Liver physiology and pathology (2 papers), Biosensors and Analytical Detection (2 papers), Advanced Neural Network Applications (2 papers), Data-Driven Disease Surveillance (2 papers), Topic Modeling (2 papers) and Advanced Image and Video Retrieval Techniques (2 papers). The work is most often cited by research in Biological Psychiatry (18 citations), Behavioral Neuroscience (7 citations), Endocrine and Autonomic Systems (12 citations), Computer Vision and Pattern Recognition (38 citations) and Hepatology (13 citations). Weicong Chen has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Haitao Sun, Xiaodan Zhong, Chunyu He, Xuemei Yang, Xu Tan, Jialing Sun, Yan Zhao, Jihong Zhu, Wenting Zhao and Xiaoyi Lu. Their work appears in journals such as Journal of Ethnopharmacology, Frontiers in Pharmacology, Theriogenology, Phytotherapy Research and Journal of Neurophysiology.
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.