Peifang Liu
- Electrical and Electronic Engineering top 5%
- Renewable Energy, Sustainability and the Environment top 5%
- Electronic, Optical and Magnetic Materials top 5%
- Materials Chemistry top 10%
- Radiology, Nuclear Medicine and Imaging top 5%
- Topics
- MRI in cancer diagnosis (20 papers)Radiomics and Machine Learning in Medical Imaging (20 papers)AI in cancer detection (14 papers)
- Cited by
- Renewable Energy, Sustainability and the EnvironmentElectrochemistryElectronic, Optical and Magnetic Materials
- Journals
- Proceedings of the National Academy of SciencesJournal of the American Chemical SocietyNature Communications
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Peifang Liu
91 papers receiving 2.7k citations
Peers
Comparison fields: 5 of 133
- Electrical and Electronic Engineering 939
- Renewable Energy, Sustainability and the Environment 583
- Electronic, Optical and Magnetic Materials 545
- Materials Chemistry 504
- Radiology, Nuclear Medicine and Imaging 477
Countries citing papers authored by Peifang Liu
This map shows the geographic impact of Peifang Liu'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 Peifang Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peifang Liu more than expected).
Fields of papers citing papers by Peifang Liu
This network shows the impact of papers produced by Peifang Liu. 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 Peifang Liu. The network helps show where Peifang Liu may publish in the future.
Co-authorship network of co-authors of Peifang Liu
This figure shows the co-authorship network connecting the top 25 collaborators of Peifang Liu. A scholar is included among the top collaborators of Peifang Liu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Peifang Liu. Peifang Liu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 15 | |
| 3 | 3 | |
| 4 | 5 | |
| 5 | 30 | |
| 6 | 18 | |
| 7 | 41 | |
| 8 | 41 | |
| 9 | 6 | |
| 10 | 30 | |
| 11 | 137 | |
| 12 | 106 | |
| 13 | 7 | |
| 14 | 2 | |
| 15 | 2 | |
| 16 | 2 | |
| 17 | 65 | |
| 18 | 52 | |
| 19 | Evaluation of Diffusion-weighted Imaging for the Differential Diagnosis of Soft-tissue Tumors | 1 |
| 20 | Angiogenesis and dynamic contrast enhanced MRI of benign and malignant breast lesions: preliminary results | 7 |
About Peifang Liu
Peifang Liu is a scholar working on Bioengineering, Radiology, Nuclear Medicine and Imaging and Electrochemistry, having authored 96 papers that have together received 2.7k indexed citations. Recurring topics across this work include MRI in cancer diagnosis (20 papers), Radiomics and Machine Learning in Medical Imaging (20 papers) and AI in cancer detection (14 papers). The work is most often cited by research in Renewable Energy, Sustainability and the Environment (583 citations), Electrochemistry (212 citations) and Electronic, Optical and Magnetic Materials (545 citations). Peifang Liu has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Fan Yang, Juntao Lu, Lin Zhuang, Yu Ji, Bing Zhu, Hai‐Ting Lu, Xin Yang, Hui Li, Maryellen L. Giger and Kaili Yao. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Nature Communications.
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.