Yong Pi
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging Techniques and Applications
Papers in
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- Radiomics and Machine Learning in Medical Imaging 6
- Medical Imaging Techniques and Applications 3
- Cardiac Imaging and Diagnostics 2
- COVID-19 diagnosis using AI 1
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- AI in cancer detection 6
- Co-authors
- Yi Zhang (8 shared papers)Xiaofeng Qi (4 shared papers)Qing Lv (3 shared papers)Yi Chen (2 shared papers)Lei Zhang (2 shared papers)Chen Yao (1 shared paper)Xiu Zhang (1 shared paper)Yali Yang (1 shared paper)
- Journals
- Knowledge-Based Systems (2 papers)Medical Image Analysis (2 papers)Neurocomputing (2 papers)Applied Intelligence (1 paper)Scientific Reports (1 paper)
- Partner nations
- China
In The Last Decade
Yong Pi
13 papers receiving 483 citations
Peers
Comparison fields: 5 of 80
- Health Informatics 43
- Radiology, Nuclear Medicine and Imaging 288
- Artificial Intelligence 232
- Renewable Energy, Sustainability and the Environment 87
- Neurology 41
Countries citing papers authored by Yong Pi
This map shows the geographic impact of Yong Pi'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 Yong Pi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yong Pi more than expected).
Fields of papers citing papers by Yong Pi
This network shows the impact of papers produced by Yong Pi. 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 Yong Pi. The network helps show where Yong Pi may publish in the future.
Co-authors
The 25 scholars most cited alongside Yong Pi, 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 | 2018 | 179 | |
| 2 | 2007 | 99 | |
| 3 | 2020 | 58 | |
| 4 | 2020 | 48 | |
| 5 | 2021 | 28 | |
| 6 | 2022 | 18 | |
| 7 | 2020 | 18 | |
| 8 | 2021 | 15 | |
| 9 | 2021 | 10 | |
| 10 | 2022 | 7 | |
| 11 | 2021 | 6 | |
| 12 | 2022 | 5 | |
| 13 | 2022 | 2 |
About Yong Pi
Yong Pi is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Computer Vision and Pattern Recognition, Pulmonary and Respiratory Medicine and Endocrinology, Diabetes and Metabolism, having authored 13 papers that have together received 493 indexed citations. Recurring topics across this work include AI in cancer detection (6 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Medical Imaging Techniques and Applications (3 papers), Medical Imaging and Pathology Studies (2 papers), Dental Radiography and Imaging (2 papers), Thyroid Cancer Diagnosis and Treatment (2 papers), Cardiac Imaging and Diagnostics (2 papers) and COVID-19 diagnosis using AI (1 paper). The work is most often cited by research in Health Informatics (43 citations), Radiology, Nuclear Medicine and Imaging (288 citations), Artificial Intelligence (232 citations), Renewable Energy, Sustainability and the Environment (87 citations) and Neurology (41 citations). Yong Pi has collaborated with scholars based in China. Frequent co-authors include Yi Zhang, Xiaofeng Qi, Qing Lv, Yi Chen, Lei Zhang, Chen Yao, Xiu Zhang, Yali Yang, Fuxiang Zhang and Naijia Guan. Their work appears in journals such as Knowledge-Based Systems, Medical Image Analysis, Neurocomputing, Applied Intelligence and Scientific Reports.
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.