Pingjun Chen
Impact in
- Health Informatics top 5%
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- Radiomics and Machine Learning in Medical Imaging
- Infrared Thermography in Medicine
Papers in
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- AI in cancer detection 7
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- Radiomics and Machine Learning in Medical Imaging 5
- Co-authors
- Lin Yang (9 shared papers)Xiaoshuang Shi (9 shared papers)Linlin Gao (1 shared paper)Kyle D. Allen (1 shared paper)Zizhao Zhang (5 shared papers)Fuyong Xing (6 shared papers)Hai Su (4 shared papers)Yuanpu Xie (4 shared papers)
- Journals
- Nature Machine Intelligence (3 papers)IEEE Transactions on Image Processing (2 papers)Laboratory Investigation (1 paper)Artificial Intelligence in Medicine (1 paper)IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)
- Partner nations
- United StatesChinaAustria
In The Last Decade
Pingjun Chen
21 papers receiving 635 citations
Peers
Comparison fields: 5 of 81
- Health Informatics 39
- Radiology, Nuclear Medicine and Imaging 214
- Rheumatology 137
- Artificial Intelligence 272
- Biophysics 47
Countries citing papers authored by Pingjun Chen
This map shows the geographic impact of Pingjun Chen'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 Pingjun Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pingjun Chen more than expected).
Fields of papers citing papers by Pingjun Chen
This network shows the impact of papers produced by Pingjun Chen. 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 Pingjun Chen. The network helps show where Pingjun Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Pingjun Chen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 198 | |
| 2 | 2019 | 193 | |
| 3 | 2018 | 32 | |
| 4 | 2019 | 30 | |
| 5 | 2019 | 29 | |
| 6 | 2020 | 28 | |
| 7 | 2020 | 27 | |
| 8 | 2020 | 27 | |
| 9 | 2021 | 16 | |
| 10 | 2024 | 14 | |
| 11 | 2021 | 13 | |
| 12 | 2022 | 11 | |
| 13 | 2022 | 7 | |
| 14 | 2020 | 5 | |
| 15 | Artificial Intelligence in Digital Pathology to Advance Cancer Immunotherapy. | 2022 | 5 |
| 16 | 2019 | 5 | |
| 17 | 2015 | 4 | |
| 18 | 2019 | 3 | |
| 19 | 2019 | 2 | |
| 20 | 2021 | 1 |
About Pingjun Chen
Pingjun Chen is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Genetics and Oncology, having authored 23 papers that have together received 651 indexed citations. Recurring topics across this work include AI in cancer detection (7 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Chronic Lymphocytic Leukemia Research (3 papers), Image Enhancement Techniques (2 papers), Osteoarthritis Treatment and Mechanisms (2 papers), Colorectal Cancer Screening and Detection (2 papers), Cell Image Analysis Techniques (2 papers) and Digital Imaging for Blood Diseases (1 paper). The work is most often cited by research in Health Informatics (39 citations), Radiology, Nuclear Medicine and Imaging (214 citations), Rheumatology (137 citations), Artificial Intelligence (272 citations) and Biophysics (47 citations). Pingjun Chen has collaborated with scholars based in United States, China and Austria. Frequent co-authors include Lin Yang, Xiaoshuang Shi, Linlin Gao, Kyle D. Allen, Zizhao Zhang, Fuyong Xing, Hai Su, Yuanpu Xie, Jinzheng Cai and Marilyn M. Bui. Their work appears in journals such as Nature Machine Intelligence, IEEE Transactions on Image Processing, Laboratory Investigation, Artificial Intelligence in Medicine and IEEE Transactions on Pattern Analysis and Machine Intelligence.
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.