Jun Feng

144 papers and 1.3k indexed citations i.

About

Jun Feng is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Jun Feng has authored 144 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Artificial Intelligence, 41 papers in Computer Vision and Pattern Recognition and 30 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Jun Feng’s work include AI in cancer detection (17 papers), Radiomics and Machine Learning in Medical Imaging (15 papers) and Sentiment Analysis and Opinion Mining (14 papers). Jun Feng is often cited by papers focused on AI in cancer detection (17 papers), Radiomics and Machine Learning in Medical Imaging (15 papers) and Sentiment Analysis and Opinion Mining (14 papers). Jun Feng collaborates with scholars based in China, United Kingdom and United States. Jun Feng's co-authors include Xia Sun, Hongyu Wang, Richard F. E. Sutcliffe, Lei Cui, Horace H. S. Ip, Yi Gao, Long Ma, Ke Dong, Su‐Shing Chen and Fan Yang and has published in prestigious journals such as Nature Communications, PLoS ONE and International Journal of Molecular Sciences.

In The Last Decade

Co-authorship network of co-authors of Jun Feng i

Fields of papers citing papers by Jun Feng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jun Feng. 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 Jun Feng. The network helps show where Jun Feng may publish in the future.

Countries citing papers authored by Jun Feng

Since Specialization
Citations

This map shows the geographic impact of Jun Feng'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 Jun Feng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Feng 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2025