Bing Fan
- Radiology, Nuclear Medicine and Imaging top 2%
- Infectious Diseases top 2%
- Neurology top 5%
- Pulmonary and Respiratory Medicine top 10%
- Artificial Intelligence top 10%
- Topics
- Radiomics and Machine Learning in Medical Imaging (23 papers)Advanced X-ray and CT Imaging (9 papers)COVID-19 diagnosis using AI (8 papers)
- Partner nations
- ChinaUnited StatesYemen
In The Last Decade
Bing Fan
65 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 118
- Radiology, Nuclear Medicine and Imaging 826
- Infectious Diseases 620
- Neurology 224
- Pulmonary and Respiratory Medicine 200
- Artificial Intelligence 195
Countries citing papers authored by Bing Fan
This map shows the geographic impact of Bing Fan'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 Bing Fan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bing Fan more than expected).
Fields of papers citing papers by Bing Fan
This network shows the impact of papers produced by Bing Fan. 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 Bing Fan. The network helps show where Bing Fan may publish in the future.
Co-authorship network of co-authors of Bing Fan
This figure shows the co-authorship network connecting the top 25 collaborators of Bing Fan. A scholar is included among the top collaborators of Bing Fan 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 Bing Fan. Bing Fan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 12 | |
| 5 | 2 | |
| 6 | 2 | |
| 7 | 0 | |
| 8 | 2 | |
| 9 | 3 | |
| 10 | 9 | |
| 11 | 1 | |
| 12 | 6 | |
| 13 | 3 | |
| 14 | 14 | |
| 15 | 17 | |
| 16 | 95 | |
| 17 | 83 | |
| 18 | 10 | |
| 19 | 42 | |
| 20 | Quantitative analysis of contrast-enhanced ultrasound in the dog's acute renal failure | 1 |
About Bing Fan
Bing Fan is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Pulmonary and Respiratory Medicine, having authored 72 papers that have together received 1.5k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (23 papers), Advanced X-ray and CT Imaging (9 papers) and COVID-19 diagnosis using AI (8 papers). The work is most often cited by research in Health Informatics (64 citations), Radiology, Nuclear Medicine and Imaging (826 citations) and Infectious Diseases (620 citations). Bing Fan has collaborated with scholars based in China, United States and Yemen. Frequent co-authors include Bingliang Zeng, Zicong Li, Chuanhong Wang, Qinglin Shen, Xiaofen Li, Honglu Li, Pinggui Lei, Jiaqi Liu, Peng Yu and Xiaoqi Lin. Their work appears in journals such as Scientific Reports, Sensors and Medical Physics.
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.