Yehang Chen
Impact in
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- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis
- COVID-19 diagnosis using AI
Papers in
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- Radiomics and Machine Learning in Medical Imaging 6
- COVID-19 diagnosis using AI 2
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- Lung Cancer Diagnosis and Treatment 5
- Gastric Cancer Management and Outcomes 2
- Co-authors
- Wansheng Long (26 shared papers)Bao Feng (23 shared papers)Xiangmeng Chen (13 shared papers)Zhuangsheng Liu (8 shared papers)Enming Cui (8 shared papers)Ronggang Li (7 shared papers)Kunwei Li (8 shared papers)Xueguo Liu (6 shared papers)
In The Last Decade
Yehang Chen
23 papers receiving 435 citations
Peers
Comparison fields: 5 of 47
- Radiology, Nuclear Medicine and Imaging 177
- Health Informatics 10
- Pulmonary and Respiratory Medicine 116
- Cancer Research 25
- Obstetrics and Gynecology 11
Countries citing papers authored by Yehang Chen
This map shows the geographic impact of Yehang 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 Yehang Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yehang Chen more than expected).
Fields of papers citing papers by Yehang Chen
This network shows the impact of papers produced by Yehang 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 Yehang Chen. The network helps show where Yehang Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Yehang 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 31 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 84 | |
| 2 | 2020 | 55 | |
| 3 | 2020 | 53 | |
| 4 | 2024 | 40 | |
| 5 | 2020 | 37 | |
| 6 | 2022 | 24 | |
| 7 | 2020 | 16 | |
| 8 | 2023 | 14 | |
| 9 | 2021 | 13 | |
| 10 | 2023 | 11 | |
| 11 | 2020 | 11 | |
| 12 | 2020 | 11 | |
| 13 | 2025 | 10 | |
| 14 | 2024 | 9 | |
| 15 | 2023 | 8 | |
| 16 | 2022 | 7 | |
| 17 | 2021 | 7 | |
| 18 | 2020 | 7 | |
| 19 | 2022 | 7 | |
| 20 | 2019 | 7 |
About Yehang Chen
Yehang Chen is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Obstetrics and Gynecology, Artificial Intelligence and Neurology, having authored 31 papers that have together received 438 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (6 papers), Lung Cancer Diagnosis and Treatment (5 papers), AI in cancer detection (3 papers), Endometrial and Cervical Cancer Treatments (3 papers), COVID-19 diagnosis using AI (2 papers), Gastric Cancer Management and Outcomes (2 papers), Myasthenia Gravis and Thymoma (2 papers) and Domain Adaptation and Few-Shot Learning (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (177 citations), Health Informatics (10 citations), Pulmonary and Respiratory Medicine (116 citations), Cancer Research (25 citations) and Obstetrics and Gynecology (11 citations). Yehang Chen has collaborated with scholars based in China and Canada. Frequent co-authors include Wansheng Long, Bao Feng, Xiangmeng Chen, Zhuangsheng Liu, Enming Cui, Ronggang Li, Kunwei Li, Xueguo Liu, Changlin Li and Kunfeng Liu. Their work appears in journals such as Frontiers in Oncology, European Radiology, Frontiers in Human Neuroscience, European Journal of Radiology and Journal of Computer Assisted Tomography.
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.