Peng Fu
Impact in
-
- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging Techniques and Applications
Papers in ⓘ
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- Radiomics and Machine Learning in Medical Imaging 8
- Advanced MRI Techniques and Applications 3
- MRI in cancer diagnosis 3
- Oncology 8
- Cancer Cells and Metastasis 2
- Co-authors
- Lin Tian (4 shared papers)Jinrui Wang (1 shared paper)Suhui Sun (1 shared paper)Sujuan Sun (1 shared paper)Min Chen (1 shared paper)Ranran Zhao (1 shared paper)Yunxue Xu (1 shared paper)Shumin Wang (1 shared paper)
- Journals
- Academic Radiology (2 papers)Molecular Imaging (2 papers)Abdominal Radiology (2 papers)Scientific Reports (1 paper)International Journal of Biological Macromolecules (1 paper)
- Partner nations
- ChinaUnited StatesThailand
In The Last Decade
Peng Fu
31 papers receiving 493 citations
Peers
Comparison fields: 5 of 77
- Radiology, Nuclear Medicine and Imaging 111
- Cancer Research 67
- Immunology 94
- Pulmonary and Respiratory Medicine 125
- Agronomy and Crop Science 36
Countries citing papers authored by Peng Fu
This map shows the geographic impact of Peng 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 Peng Fu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peng Fu more than expected).
Fields of papers citing papers by Peng Fu
This network shows the impact of papers produced by Peng 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 Peng Fu. The network helps show where Peng Fu may publish in the future.
Co-authors
The 25 scholars most cited alongside Peng 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 37 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 79 | |
| 2 | 2000 | 68 | |
| 3 | 2013 | 64 | |
| 4 | 2019 | 36 | |
| 5 | 2010 | 25 | |
| 6 | 2016 | 24 | |
| 7 | 2022 | 21 | |
| 8 | 2021 | 19 | |
| 9 | 2022 | 18 | |
| 10 | 2021 | 15 | |
| 11 | 2023 | 13 | |
| 12 | 2021 | 13 | |
| 13 | 2024 | 12 | |
| 14 | 2022 | 11 | |
| 15 | 2015 | 10 | |
| 16 | 2021 | 9 | |
| 17 | 2021 | 9 | |
| 18 | 2024 | 8 | |
| 19 | 2016 | 8 | |
| 20 | 2015 | 7 |
About Peng Fu
Peng Fu is a scholar working on Radiology, Nuclear Medicine and Imaging, Oncology, Cancer Research, Neurology and Pharmacology, having authored 37 papers that have together received 502 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (8 papers), Advanced MRI Techniques and Applications (3 papers), MRI in cancer diagnosis (3 papers), RNA modifications and cancer (3 papers), Lung Cancer Diagnosis and Treatment (3 papers), Cancer Cells and Metastasis (2 papers), Neurological disorders and treatments (2 papers) and Renal cell carcinoma treatment (2 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (111 citations), Cancer Research (67 citations), Immunology (94 citations), Pulmonary and Respiratory Medicine (125 citations) and Agronomy and Crop Science (36 citations). Peng Fu has collaborated with scholars based in China, United States and Thailand. Frequent co-authors include Lin Tian, Jinrui Wang, Suhui Sun, Sujuan Sun, Min Chen, Ranran Zhao, Yunxue Xu, Shumin Wang, Xiaolong Liang and Mingji Yi. Their work appears in journals such as Academic Radiology, Molecular Imaging, Abdominal Radiology, Scientific Reports and International Journal of Biological Macromolecules.
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.