Kai Fu
Impact in
- Immunology top 10%
- Immune Cell Function and Interaction
- Immunotherapy and Immune Responses
- Phagocytosis and Immune Regulation
- Immune cells in cancer
- Oncology top 10%
- Cancer Immunotherapy and Biomarkers
- CAR-T cell therapy research
Papers in
- Oncology 7
- Cancer Immunotherapy and Biomarkers 3
- Viral-associated cancers and disorders 2
- CAR-T cell therapy research 2
-
- Immune Cell Function and Interaction 4
- T-cell and Retrovirus Studies 2
- Immune cells in cancer 2
- Co-authors
- Zhenhua Ren (2 shared papers)Yan Luan (2 shared papers)Chuanhui Han (1 shared paper)Zhida Liu (1 shared paper)Ting Xu (1 shared paper)Yang‐Xin Fu (1 shared paper)Chunbo Dong (1 shared paper)Anli Zhang (1 shared paper)
- Journals
- Clinical Immunology (2 papers)JNCI Journal of the National Cancer Institute (1 paper)Acta Pharmaceutica Sinica B (1 paper)Cell Reports (1 paper)Frontiers in Public Health (1 paper)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Kai Fu
16 papers receiving 579 citations
Peers
Comparison fields: 5 of 107
- Immunology 246
- Oncology 217
- Pathology and Forensic Medicine 80
- Parasitology 22
- Cancer Research 45
Countries citing papers authored by Kai Fu
This map shows the geographic impact of Kai Fu'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 Kai Fu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kai Fu more than expected).
Fields of papers citing papers by Kai Fu
This network shows the impact of papers produced by Kai Fu. 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 Kai Fu. The network helps show where Kai Fu may publish in the future.
Co-authors
The 25 scholars most cited alongside Kai Fu, 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 | 2019 | 137 | |
| 2 | 2018 | 111 | |
| 3 | 2020 | 70 | |
| 4 | 2015 | 66 | |
| 5 | 2014 | 62 | |
| 6 | 2016 | 52 | |
| 7 | 2023 | 34 | |
| 8 | 2013 | 15 | |
| 9 | 2022 | 14 | |
| 10 | 2015 | 8 | |
| 11 | 2023 | 7 | |
| 12 | 2024 | 4 | |
| 13 | 2022 | 2 | |
| 14 | 2023 | 2 | |
| 15 | 2016 | 1 | |
| 16 | 2017 | 1 | |
| 17 | 2024 | 0 | |
| 18 | 2023 | 0 | |
| 19 | 2025 | 0 | |
| 20 | 2025 | 0 |
About Kai Fu
Kai Fu is a scholar working on Oncology, Immunology, Pathology and Forensic Medicine, Pulmonary and Respiratory Medicine and Cancer Research, having authored 20 papers that have together received 586 indexed citations. Recurring topics across this work include Lymphoma Diagnosis and Treatment (5 papers), Immune Cell Function and Interaction (4 papers), Cancer Immunotherapy and Biomarkers (3 papers), T-cell and Retrovirus Studies (2 papers), Viral-associated cancers and disorders (2 papers), Immune cells in cancer (2 papers), CAR-T cell therapy research (2 papers) and Lung Cancer Diagnosis and Treatment (2 papers). The work is most often cited by research in Immunology (246 citations), Oncology (217 citations), Pathology and Forensic Medicine (80 citations), Parasitology (22 citations) and Cancer Research (45 citations). Kai Fu has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Zhenhua Ren, Yan Luan, Chuanhui Han, Zhida Liu, Ting Xu, Yang‐Xin Fu, Chunbo Dong, Anli Zhang, Casey Moore and Jian Qiao. Their work appears in journals such as Clinical Immunology, JNCI Journal of the National Cancer Institute, Acta Pharmaceutica Sinica B, Cell Reports and Frontiers in Public Health.
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.