Canyu Chen
Impact in
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- Topic Modeling
Papers in
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- Topic Modeling 4
- Natural Language Processing Techniques 2
- Authorship Attribution and Profiling 2
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- Metabolism, Diabetes, and Cancer 2
- Co-authors
- Kai Shu (8 shared papers)Lichao Sun (1 shared paper)Anming Wang (1 shared paper)Yu‐Guo Zheng (1 shared paper)Xiaolin Pei (1 shared paper)Philip S. Yu (1 shared paper)Yingtong Dou (1 shared paper)Stephen Gang Wu (1 shared paper)
- Journals
- AI Magazine (1 paper)Journal of Molecular Catalysis B Enzymatic (1 paper)Materials & Design (1 paper)Immunopharmacology and Immunotoxicology (1 paper)Renal Failure (1 paper)
- Partner nations
- ChinaUnited StatesBosnia and Herzegovina
In The Last Decade
Canyu Chen
22 papers receiving 202 citations
Canyu Chen's Hit Papers
Peers
Comparison fields: 5 of 74
- Health Informatics 5
- Artificial Intelligence 62
- Information Systems 35
- Health Information Management 6
- General Social Sciences 4
Countries citing papers authored by Canyu Chen
This map shows the geographic impact of Canyu 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 Canyu Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Canyu Chen more than expected).
Fields of papers citing papers by Canyu Chen
This network shows the impact of papers produced by Canyu 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 Canyu Chen. The network helps show where Canyu Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Canyu 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Combating misinformation in the age of LLMs: Opportunities and challenges Hit paper breakdown → | 2024 | 51 |
| 2 | 2023 | 23 | |
| 3 | 2016 | 21 | |
| 4 | 2022 | 19 | |
| 5 | 2022 | 13 | |
| 6 | 2021 | 11 | |
| 7 | 2023 | 9 | |
| 8 | 2024 | 8 | |
| 9 | 2024 | 8 | |
| 10 | 2025 | 7 | |
| 11 | 2023 | 6 | |
| 12 | 2021 | 5 | |
| 13 | 2012 | 5 | |
| 14 | 2023 | 4 | |
| 15 | 2025 | 4 | |
| 16 | 2025 | 3 | |
| 17 | 2024 | 3 | |
| 18 | 2012 | 3 | |
| 19 | 2024 | 2 | |
| 20 | 2025 | 1 |
About Canyu Chen
Canyu Chen is a scholar working on Artificial Intelligence, Molecular Biology, Physiology, Organic Chemistry and Surgery, having authored 26 papers that have together received 208 indexed citations. Recurring topics across this work include Topic Modeling (4 papers), Metabolism, Diabetes, and Cancer (2 papers), Natural Language Processing Techniques (2 papers), Spam and Phishing Detection (2 papers), Misinformation and Its Impacts (2 papers), Authorship Attribution and Profiling (2 papers), Diabetes Management and Research (1 paper) and Software System Performance and Reliability (1 paper). The work is most often cited by research in Health Informatics (5 citations), Artificial Intelligence (62 citations), Information Systems (35 citations), Health Information Management (6 citations) and General Social Sciences (4 citations). Canyu Chen has collaborated with scholars based in China, United States and Bosnia and Herzegovina. Frequent co-authors include Kai Shu, Lichao Sun, Anming Wang, Yu‐Guo Zheng, Xiaolin Pei, Philip S. Yu, Yingtong Dou, Stephen Gang Wu, Jiecan Zhou and Mohammad Reza Askari. Their work appears in journals such as AI Magazine, Journal of Molecular Catalysis B Enzymatic, Materials & Design, Immunopharmacology and Immunotoxicology and Renal Failure.
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.