Feicheng Wang
Impact in
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- Cancer Immunotherapy and Biomarkers
- Colorectal Cancer Treatments and Studies
- CAR-T cell therapy research
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- Model Reduction and Neural Networks
Papers in
- Oncology 3
- Cancer Immunotherapy and Biomarkers 3
- Colorectal Cancer Treatments and Studies 2
- Pancreatic and Hepatic Oncology Research 1
- Co-authors
- Zhiqiang Hu (1 shared paper)Liwei Wang (1 shared paper)Lu Zhou (1 shared paper)Hongming Pu (1 shared paper)Kun‐Hsing Yu (4 shared papers)Shawn G. Kwatra (2 shared papers)Yevgeniy R. Semenov (2 shared papers)Vartan Pahalyants (2 shared papers)
- Journals
- Journal of the American Academy of Dermatology (1 paper)Sensors (1 paper)npj Precision Oncology (1 paper)Journal for ImmunoTherapy of Cancer (1 paper)International Journal of Cancer (1 paper)
- Partner nations
- ChinaUnited States
In The Last Decade
Feicheng Wang
6 papers receiving 332 citations
Peers
Comparison fields: 5 of 92
- Oncology 118
- Statistical and Nonlinear Physics 39
- Artificial Intelligence 99
- Computer Vision and Pattern Recognition 43
- Structural Biology 2
Countries citing papers authored by Feicheng Wang
This map shows the geographic impact of Feicheng 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 Feicheng Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Feicheng Wang more than expected).
Fields of papers citing papers by Feicheng Wang
This network shows the impact of papers produced by Feicheng 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 Feicheng Wang. The network helps show where Feicheng Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Feicheng 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
| # | Work | ||
|---|---|---|---|
| 1 | The expressive power of neural networks: a view from the width | 2017 | 193 |
| 2 | 2021 | 57 | |
| 3 | 2021 | 57 | |
| 4 | 2021 | 24 | |
| 5 | 2023 | 10 | |
| 6 | 2021 | 2 | |
| 7 | 2024 | 0 | |
| 8 | 2023 | 0 | |
| 9 | 2023 | 0 |
About Feicheng Wang
Feicheng Wang is a scholar working on Oncology, Electrical and Electronic Engineering, Mechanical Engineering, Infectious Diseases and Automotive Engineering, having authored 9 papers that have together received 343 indexed citations. Recurring topics across this work include Cancer Immunotherapy and Biomarkers (3 papers), Colorectal Cancer Treatments and Studies (2 papers), Additive Manufacturing Materials and Processes (1 paper), Neural Networks and Applications (1 paper), Lung Cancer Treatments and Mutations (1 paper), Calibration and Measurement Techniques (1 paper), Pancreatic and Hepatic Oncology Research (1 paper) and Optical Polarization and Ellipsometry (1 paper). The work is most often cited by research in Oncology (118 citations), Statistical and Nonlinear Physics (39 citations), Artificial Intelligence (99 citations), Computer Vision and Pattern Recognition (43 citations) and Structural Biology (2 citations). Feicheng Wang has collaborated with scholars based in China and United States. Frequent co-authors include Zhiqiang Hu, Liwei Wang, Lu Zhou, Hongming Pu, Kun‐Hsing Yu, Shawn G. Kwatra, Yevgeniy R. Semenov, Vartan Pahalyants, Mark Kalinich and Shannon Wongvibulsin. Their work appears in journals such as Journal of the American Academy of Dermatology, Sensors, npj Precision Oncology, Journal for ImmunoTherapy of Cancer and International Journal of Cancer.
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.