Beiyi Shen
Impact in
- Health Informatics top 5%
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- COVID-19 diagnosis using AI
- Radiomics and Machine Learning in Medical Imaging
Papers in
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- COVID-19 diagnosis using AI 4
- Radiomics and Machine Learning in Medical Imaging 2
- Radiology practices and education 2
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- COVID-19 Clinical Research Studies 3
- Co-authors
- Timothy Q. Duong (5 shared papers)Almas Abbasi (4 shared papers)Haifang Li (3 shared papers)Jocelyn Zhu (2 shared papers)T. K. B. Gandhi (1 shared paper)Shilpa Nagaraju (1 shared paper)Malabika Sarker (1 shared paper)Giovanni Parmigiani (1 shared paper)
- Journals
- Clinical Cancer Research (1 paper)PeerJ (1 paper)Clinical Radiology (1 paper)PLoS ONE (1 paper)Nature Genetics (1 paper)
- Partner nations
- United StatesGermanyIndia
In The Last Decade
Beiyi Shen
9 papers receiving 563 citations
Peers
Comparison fields: 5 of 82
- Health Informatics 27
- Radiology, Nuclear Medicine and Imaging 154
- Aging 8
- Molecular Biology 304
- Computational Theory and Mathematics 55
Countries citing papers authored by Beiyi Shen
This map shows the geographic impact of Beiyi Shen'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 Beiyi Shen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Beiyi Shen more than expected).
Fields of papers citing papers by Beiyi Shen
This network shows the impact of papers produced by Beiyi Shen. 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 Beiyi Shen. The network helps show where Beiyi Shen may publish in the future.
Co-authors
The 25 scholars most cited alongside Beiyi Shen, 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 | 2006 | 338 | |
| 2 | 2020 | 107 | |
| 3 | 2021 | 38 | |
| 4 | 2020 | 29 | |
| 5 | 2016 | 23 | |
| 6 | 2021 | 22 | |
| 7 | 2021 | 12 | |
| 8 | 2023 | 5 | |
| 9 | 2020 | 2 | |
| 10 | 2022 | 0 |
About Beiyi Shen
Beiyi Shen is a scholar working on Radiology, Nuclear Medicine and Imaging, Infectious Diseases, Molecular Biology, Neurology and Genetics, having authored 10 papers that have together received 576 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (4 papers), COVID-19 Clinical Research Studies (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Radiology practices and education (2 papers), Amyotrophic Lateral Sclerosis Research (1 paper), Phytochemicals and Antioxidant Activities (1 paper), Chemokine receptors and signaling (1 paper) and Pneumonia and Respiratory Infections (1 paper). The work is most often cited by research in Health Informatics (27 citations), Radiology, Nuclear Medicine and Imaging (154 citations), Aging (8 citations), Molecular Biology (304 citations) and Computational Theory and Mathematics (55 citations). Beiyi Shen has collaborated with scholars based in United States, Germany and India. Frequent co-authors include Timothy Q. Duong, Almas Abbasi, Haifang Li, Jocelyn Zhu, T. K. B. Gandhi, Shilpa Nagaraju, Malabika Sarker, Giovanni Parmigiani, Stefan Pinkert and Kannabiran Nandakumar. Their work appears in journals such as Clinical Cancer Research, PeerJ, Clinical Radiology, PLoS ONE and Nature Genetics.
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.