Zilong Wang
Impact in
- Artificial Intelligence top 10%
- Sentiment Analysis and Opinion Mining
- Topic Modeling
- Advanced Text Analysis Techniques
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- Emotion and Mood Recognition
Papers in
-
- Topic Modeling 4
- Natural Language Processing Techniques 2
- Sentiment Analysis and Opinion Mining 2
- Genetics 5
- Glioma Diagnosis and Treatment 5
- Co-authors
- Xiaojun Wan (1 shared paper)Jie Sheng (1 shared paper)Ping Yu (1 shared paper)Zhijiang Zeng (1 shared paper)Weiyu Yan (1 shared paper)Qing Yan (1 shared paper)Huajun Zheng (1 shared paper)Yongqiang Zhu (1 shared paper)
- Journals
- CNS Neuroscience & Therapeutics (2 papers)ACS Synthetic Biology (1 paper)Nature Communications (1 paper)Frontiers in Public Health (1 paper)Frontiers in Psychology (1 paper)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Zilong Wang
22 papers receiving 253 citations
Peers
Comparison fields: 5 of 80
- Artificial Intelligence 131
- Experimental and Cognitive Psychology 42
- Signal Processing 32
- Genetics 17
- Computational Mathematics 1
Countries citing papers authored by Zilong Wang
This map shows the geographic impact of Zilong Wang'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 Zilong Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zilong Wang more than expected).
Fields of papers citing papers by Zilong Wang
This network shows the impact of papers produced by Zilong Wang. 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 Zilong Wang. The network helps show where Zilong Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Zilong Wang, 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 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 114 | |
| 2 | 2020 | 20 | |
| 3 | 2020 | 19 | |
| 4 | 2018 | 12 | |
| 5 | 2021 | 11 | |
| 6 | 2023 | 9 | |
| 7 | 2023 | 9 | |
| 8 | 2023 | 9 | |
| 9 | 2023 | 8 | |
| 10 | 2022 | 7 | |
| 11 | 2024 | 6 | |
| 12 | 2023 | 5 | |
| 13 | 2022 | 5 | |
| 14 | 2024 | 4 | |
| 15 | 2023 | 4 | |
| 16 | 2024 | 3 | |
| 17 | 2024 | 3 | |
| 18 | 2023 | 3 | |
| 19 | 2023 | 3 | |
| 20 | 2024 | 1 |
About Zilong Wang
Zilong Wang is a scholar working on Artificial Intelligence, Genetics, Epidemiology, Molecular Biology and Pulmonary and Respiratory Medicine, having authored 25 papers that have together received 257 indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (5 papers), Topic Modeling (4 papers), Liver Disease Diagnosis and Treatment (3 papers), Ferroptosis and cancer prognosis (2 papers), Natural Language Processing Techniques (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Sentiment Analysis and Opinion Mining (2 papers) and Behavioral Health and Interventions (1 paper). The work is most often cited by research in Artificial Intelligence (131 citations), Experimental and Cognitive Psychology (42 citations), Signal Processing (32 citations), Genetics (17 citations) and Computational Mathematics (1 citation). Zilong Wang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Xiaojun Wan, Jie Sheng, Ping Yu, Zhijiang Zeng, Weiyu Yan, Qing Yan, Huajun Zheng, Yongqiang Zhu, Ming Yang and Yu Guo. Their work appears in journals such as CNS Neuroscience & Therapeutics, ACS Synthetic Biology, Nature Communications, Frontiers in Public Health and Frontiers in Psychology.
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.