Bing Ji

104 papers receiving 1.8k citations

Peers

Bing Ji
Comparison fields: 5 of 154
  • Health Informatics 17
  • Computer Vision and Pattern Recognition 251
  • Biological Psychiatry 31
  • Radiology, Nuclear Medicine and Imaging 201
  • Cancer Research 131
Replace Xiong Zhang with:
Xiong Zhang China
Jianwei Lu China
Zhe Zhang China
Lei Cai China
Guangzhi Wang China
Kelvin Wong United States
Min Du China
Michael Wainberg Canada
Xiuli Li China
Jing Qin China
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Citations per field
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Citations per year

Countries citing papers authored by Bing Ji

Since Specialization
Citations

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

Fields of papers citing papers by Bing Ji

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Bing Ji, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Bing Ji Line = papers co-authored together Bing Ji links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 117 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014213
2 2020126
3 201799
4 202176
5 201759
6
FOXC1 promotes proliferation and epithelial-mesenchymal transition in cervical carcinoma through the PI3K-AKT signal pathway.
201753
7 201550
8 201947
9 201946
10 201846
11 202043
12 201142
13 201940
14 201639
15 201839
16
Tissue of origin dictates branched-chain amino acid metabolism in mutant Kras-driven cancers
201634
17 201632
18 202131
19 202031
20 202230

About Bing Ji

Bing Ji is a scholar working on Radiology, Nuclear Medicine and Imaging, Health Informatics, Computer Vision and Pattern Recognition, Oncology and Hepatology, having authored 117 papers that have together received 1.8k indexed citations. Recurring topics across this work include Biomimetic flight and propulsion mechanisms (7 papers), Bone health and treatments (7 papers), Functional Brain Connectivity Studies (6 papers), Advanced MRI Techniques and Applications (6 papers), EEG and Brain-Computer Interfaces (5 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Bone health and osteoporosis research (4 papers) and Advanced X-ray and CT Imaging (4 papers). The work is most often cited by research in Health Informatics (17 citations), Computer Vision and Pattern Recognition (251 citations), Biological Psychiatry (31 citations), Radiology, Nuclear Medicine and Imaging (201 citations) and Cancer Research (131 citations). Bing Ji has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Yibin Li, Xin Ma, Haibo Wang, Yueming Sun, Chuan Zhang, Yongfeng Zhang, Menghua Zhang, Xingong Cheng, Jinkui Feng and Yongling An. Their work appears in journals such as Computer Methods and Programs in Biomedicine, Oncology Reports, Information Sciences, Aerospace Science and Technology and IEEE Access.

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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