Bing Fan

62 papers and 1.3k indexed citations i.

About

Bing Fan is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Surgery. According to data from OpenAlex, Bing Fan has authored 62 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Radiology, Nuclear Medicine and Imaging, 19 papers in Pulmonary and Respiratory Medicine and 13 papers in Surgery. Recurrent topics in Bing Fan’s work include Radiomics and Machine Learning in Medical Imaging (20 papers), COVID-19 diagnosis using AI (8 papers) and Advanced X-ray and CT Imaging (7 papers). Bing Fan is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (20 papers), COVID-19 diagnosis using AI (8 papers) and Advanced X-ray and CT Imaging (7 papers). Bing Fan collaborates with scholars based in China, South Korea and Yemen. Bing Fan's co-authors include Bingliang Zeng, Zicong Li, Chuanhong Wang, Qinglin Shen, Xiaofen Li, Honglu Li, Pinggui Lei, Peng Yu, Jiaqi Liu and Xiaoqi Lin and has published in prestigious journals such as Scientific Reports, Sensors and Medicine.

In The Last Decade

Co-authorship network of co-authors of Bing Fan i

Fields of papers citing papers by Bing Fan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Countries citing papers authored by Bing Fan

Since Specialization
Citations

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).

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.

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2025