Sirui Fu
Impact in
- Hepatology top 5%
- Hepatocellular Carcinoma Treatment and Prognosis
- Liver Disease and Transplantation
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- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
Papers in
- Hepatology 23
- Hepatocellular Carcinoma Treatment and Prognosis 16
- Liver Disease and Transplantation 6
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- Radiomics and Machine Learning in Medical Imaging 6
- MRI in cancer diagnosis 2
- Co-authors
- Ligong Lu (24 shared papers)Meixiao Zhan (6 shared papers)Yongjie Xin (3 shared papers)Zaiyi Liu (3 shared papers)Shuting Chen (3 shared papers)Wei Zhao (1 shared paper)Wenjun Ni (1 shared paper)Wei Li (1 shared paper)
- Journals
- Hepatology International (3 papers)Oncotarget (3 papers)Journal of Clinical Oncology (1 paper)Medicine (1 paper)Engineering Applications of Artificial Intelligence (1 paper)
- Partner nations
- ChinaUnited States
In The Last Decade
Sirui Fu
27 papers receiving 548 citations
Peers
Comparison fields: 5 of 56
- Hepatology 217
- Cancer Research 124
- Health Informatics 5
- Radiology, Nuclear Medicine and Imaging 75
- Oncology 73
Countries citing papers authored by Sirui Fu
This map shows the geographic impact of Sirui 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 Sirui Fu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sirui Fu more than expected).
Fields of papers citing papers by Sirui Fu
This network shows the impact of papers produced by Sirui 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 Sirui Fu. The network helps show where Sirui Fu may publish in the future.
Co-authors
The 25 scholars most cited alongside Sirui 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
Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 137 | |
| 2 | 2015 | 61 | |
| 3 | 2018 | 44 | |
| 4 | 2016 | 39 | |
| 5 | 2014 | 31 | |
| 6 | 2016 | 28 | |
| 7 | 2017 | 28 | |
| 8 | 2014 | 24 | |
| 9 | 2017 | 23 | |
| 10 | 2021 | 22 | |
| 11 | 2021 | 22 | |
| 12 | 2016 | 19 | |
| 13 | 2020 | 15 | |
| 14 | 2019 | 13 | |
| 15 | 2021 | 7 | |
| 16 | 2015 | 7 | |
| 17 | 2023 | 6 | |
| 18 | 2022 | 6 | |
| 19 | 2021 | 6 | |
| 20 | 2024 | 4 |
About Sirui Fu
Sirui Fu is a scholar working on Hepatology, Radiology, Nuclear Medicine and Imaging, Molecular Biology, Pulmonary and Respiratory Medicine and Epidemiology, having authored 30 papers that have together received 552 indexed citations. Recurring topics across this work include Hepatocellular Carcinoma Treatment and Prognosis (16 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Liver Disease and Transplantation (6 papers), Liver Disease Diagnosis and Treatment (3 papers), MRI in cancer diagnosis (2 papers), Lung Cancer Diagnosis and Treatment (2 papers), Cancer Mechanisms and Therapy (2 papers) and Organ Transplantation Techniques and Outcomes (1 paper). The work is most often cited by research in Hepatology (217 citations), Cancer Research (124 citations), Health Informatics (5 citations), Radiology, Nuclear Medicine and Imaging (75 citations) and Oncology (73 citations). Sirui Fu has collaborated with scholars based in China and United States. Frequent co-authors include Ligong Lu, Meixiao Zhan, Yongjie Xin, Zaiyi Liu, Shuting Chen, Wei Zhao, Wenjun Ni, Wei Li, Yong Li and Bao‐Shan Hu. Their work appears in journals such as Hepatology International, Oncotarget, Journal of Clinical Oncology, Medicine and Engineering Applications of Artificial Intelligence.
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.