Feiyan Li
Impact in
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
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- Organic Light-Emitting Diodes Research 5
- Photonic and Optical Devices 4
- Co-authors
- Weisheng Li (15 shared papers)Linhong Wang (3 shared papers)Shengfeng Qin (4 shared papers)Kun Hu (2 shared papers)Zhong Zhang (2 shared papers)Yinghui Zhao (3 shared papers)Jianzhong Fan (5 shared papers)Chuan‐Kui Wang (5 shared papers)
In The Last Decade
Feiyan Li
65 papers receiving 665 citations
Peers
Comparison fields: 5 of 114
- Instrumentation 23
- Radiology, Nuclear Medicine and Imaging 126
- Computer Vision and Pattern Recognition 119
- Oncology 110
- Physical and Theoretical Chemistry 32
Countries citing papers authored by Feiyan Li
This map shows the geographic impact of Feiyan Li'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 Feiyan Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Feiyan Li more than expected).
Fields of papers citing papers by Feiyan Li
This network shows the impact of papers produced by Feiyan Li. 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 Feiyan Li. The network helps show where Feiyan Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Feiyan Li, 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 75 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 48 | |
| 2 | 2021 | 43 | |
| 3 | 2017 | 39 | |
| 4 | 2019 | 36 | |
| 5 | 2022 | 33 | |
| 6 | 2019 | 33 | |
| 7 | 2016 | 23 | |
| 8 | 2015 | 21 | |
| 9 | 2022 | 20 | |
| 10 | 2019 | 20 | |
| 11 | 2024 | 19 | |
| 12 | 2013 | 18 | |
| 13 | 2021 | 16 | |
| 14 | 2023 | 15 | |
| 15 | 2019 | 15 | |
| 16 | 2019 | 13 | |
| 17 | 2021 | 13 | |
| 18 | 2021 | 12 | |
| 19 | 2020 | 12 | |
| 20 | 2019 | 12 |
About Feiyan Li
Feiyan Li is a scholar working on Electrical and Electronic Engineering, Biomedical Engineering, Radiology, Nuclear Medicine and Imaging, Molecular Biology and Computer Vision and Pattern Recognition, having authored 75 papers that have together received 677 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (6 papers), Quantum Information and Cryptography (5 papers), Organic Light-Emitting Diodes Research (5 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Photonic and Optical Devices (4 papers), Traditional Chinese Medicine Analysis (4 papers), Luminescence and Fluorescent Materials (4 papers) and Medical Image Segmentation Techniques (3 papers). The work is most often cited by research in Instrumentation (23 citations), Radiology, Nuclear Medicine and Imaging (126 citations), Computer Vision and Pattern Recognition (119 citations), Oncology (110 citations) and Physical and Theoretical Chemistry (32 citations). Feiyan Li has collaborated with scholars based in China, Australia and Singapore. Frequent co-authors include Weisheng Li, Linhong Wang, Shengfeng Qin, Kun Hu, Zhong Zhang, Yinghui Zhao, Jianzhong Fan, Chuan‐Kui Wang, Lili Lin and Guanyu Jiang. Their work appears in journals such as Biomedical Signal Processing and Control, Chinese Journal of Natural Medicines, Knowledge-Based Systems, Medical Physics and Expert Systems with Applications.
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.