Liyao Fu
Impact in
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- Diabetes, Cardiovascular Risks, and Lipoproteins
- Diabetes Treatment and Management
Papers in
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- Cardiovascular Function and Risk Factors 3
- Heart Failure Treatment and Management 2
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- Diabetes Treatment and Management 2
- Diabetes, Cardiovascular Risks, and Lipoproteins 2
- Co-authors
- Shi Tai (15 shared papers)Ningjie Zhang (5 shared papers)Zhenhua Xing (8 shared papers)Yongjun Wang (6 shared papers)Ying Zhou (6 shared papers)Yang Feng (3 shared papers)Jiaxing Sun (6 shared papers)Yongjun Wang (2 shared papers)
In The Last Decade
Liyao Fu
22 papers receiving 505 citations
Peers
Comparison fields: 5 of 87
- Endocrinology, Diabetes and Metabolism 78
- Nephrology 32
- Cardiology and Cardiovascular Medicine 79
- Neurology 26
- Geriatrics and Gerontology 7
Countries citing papers authored by Liyao Fu
This map shows the geographic impact of Liyao 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 Liyao Fu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Liyao Fu more than expected).
Fields of papers citing papers by Liyao Fu
This network shows the impact of papers produced by Liyao 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 Liyao Fu. The network helps show where Liyao Fu may publish in the future.
Co-authors
The 25 scholars most cited alongside Liyao 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 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 88 | |
| 2 | 2022 | 54 | |
| 3 | 2022 | 53 | |
| 4 | 2022 | 48 | |
| 5 | 2023 | 41 | |
| 6 | 2017 | 41 | |
| 7 | 2024 | 33 | |
| 8 | 2022 | 32 | |
| 9 | 2022 | 24 | |
| 10 | 2023 | 20 | |
| 11 | 2020 | 12 | |
| 12 | 2024 | 12 | |
| 13 | 2024 | 11 | |
| 14 | 2021 | 10 | |
| 15 | 2020 | 7 | |
| 16 | 2022 | 5 | |
| 17 | 2021 | 5 | |
| 18 | 2024 | 4 | |
| 19 | 2014 | 4 | |
| 20 | 2024 | 3 |
About Liyao Fu
Liyao Fu is a scholar working on Cardiology and Cardiovascular Medicine, Endocrinology, Diabetes and Metabolism, Molecular Biology, Computer Vision and Pattern Recognition and Nephrology, having authored 22 papers that have together received 509 indexed citations. Recurring topics across this work include Cardiovascular Function and Risk Factors (3 papers), Diabetes Treatment and Management (2 papers), Heart Failure Treatment and Management (2 papers), Immune cells in cancer (2 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (2 papers), Advanced Neural Network Applications (2 papers), Streptococcal Infections and Treatments (1 paper) and Medical Image Segmentation Techniques (1 paper). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (78 citations), Nephrology (32 citations), Cardiology and Cardiovascular Medicine (79 citations), Neurology (26 citations) and Geriatrics and Gerontology (7 citations). Liyao Fu has collaborated with scholars based in China and Finland. Frequent co-authors include Shi Tai, Ningjie Zhang, Zhenhua Xing, Yongjun Wang, Ying Zhou, Yang Feng, Jiaxing Sun, Yongjun Wang, Shenghua Zhou and Zhaowei Zhu. Their work appears in journals such as Cardiovascular Diabetology, Frontiers in Cardiovascular Medicine, Cardiovascular Therapeutics, Biomedical Signal Processing and Control and iScience.
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.