Baojun Li
Impact in
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- Radiomics and Machine Learning in Medical Imaging
- Radiation Dose and Imaging
- Medical Imaging Techniques and Applications
- MRI in cancer diagnosis
- Otorhinolaryngology top 5%
- Head and Neck Cancer Studies
Papers in
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- Radiation Dose and Imaging 19
- Medical Imaging Techniques and Applications 14
- Radiomics and Machine Learning in Medical Imaging 12
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- Head and Neck Cancer Studies 4
- Co-authors
- Muhammad M. QureshiKaren BuchOsamu SakaiStephan W. AndersonJorge A. SotoJiang HsiehHeiShun YuHirofumi Kuno
- Journals
- Medical Physics (8 papers)European Journal of Radiology (4 papers)American Journal of Neuroradiology (3 papers)Academic Radiology (2 papers)Journal of Magnetic Resonance Imaging (2 papers)
- Partner nations
- United StatesJapanChina
In The Last Decade
Baojun Li
43 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 91
- Radiology, Nuclear Medicine and Imaging 901
- Otorhinolaryngology 109
- Biomedical Engineering 552
- Oral Surgery 81
- Hepatology 85
Countries citing papers authored by Baojun Li
This map shows the geographic impact of Baojun Li'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 Baojun Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Baojun Li more than expected).
Fields of papers citing papers by Baojun Li
This network shows the impact of papers produced by Baojun Li. 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 Baojun Li. The network helps show where Baojun Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Baojun Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 5 | |
| 2 | 2023 | 1 | |
| 3 | 2023 | 0 | |
| 4 | 2022 | 7 | |
| 5 | 2020 | 14 | |
| 6 | 2019 | 32 | |
| 7 | 2019 | 25 | |
| 8 | 2019 | 22 | |
| 9 | 2018 | 11 | |
| 10 | 2018 | 7 | |
| 11 | 2017 | 70 | |
| 12 | 2017 | 44 | |
| 13 | 2017 | 126 | |
| 14 | 2015 | 71 | |
| 15 | 2015 | 5 | |
| 16 | 2013 | 6 | |
| 17 | 2012 | 19 | |
| 18 | 2012 | 9 | |
| 19 | 2007 | 24 | |
| 20 | Orbital maintenance and control of spacecraft fly-around with finite-thrust | 2007 | 0 |
About Baojun Li
Baojun Li is a scholar working on Radiology, Nuclear Medicine and Imaging, Otorhinolaryngology, Biomedical Engineering, Hepatology and Oral Surgery, having authored 45 papers that have together received 1.2k indexed citations. Recurring topics across this work include Advanced X-ray and CT Imaging (21 papers), Radiation Dose and Imaging (19 papers), Medical Imaging Techniques and Applications (14 papers), Radiomics and Machine Learning in Medical Imaging (12 papers), Liver Disease Diagnosis and Treatment (5 papers), Head and Neck Cancer Studies (4 papers), Hepatocellular Carcinoma Treatment and Prognosis (3 papers) and Hepatitis B Virus Studies (3 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (901 citations), Otorhinolaryngology (109 citations), Biomedical Engineering (552 citations), Oral Surgery (81 citations) and Hepatology (85 citations). Baojun Li has collaborated with scholars based in United States, Japan and China. Frequent co-authors include Muhammad M. Qureshi, Karen Buch, Osamu Sakai, Stephan W. Anderson, Jorge A. Soto, Jiang Hsieh, HeiShun Yu, Hirofumi Kuno, G Yadava and Margaret N. Chapman. Their work appears in journals such as Medical Physics, European Journal of Radiology, American Journal of Neuroradiology, Academic Radiology and Journal of Magnetic Resonance Imaging.
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.