Yaopan Wu
Impact in
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- MRI in cancer diagnosis
- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging Techniques and Applications
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- Gastrointestinal Tumor Research and Treatment
Papers in
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- MRI in cancer diagnosis 4
- Radiomics and Machine Learning in Medical Imaging 4
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- Breast Cancer Treatment Studies 2
- Co-authors
- Ni He (12 shared papers)Li Li (3 shared papers)Hongmin Cai (2 shared papers)Peiqiang Cai (6 shared papers)Jieting Chen (5 shared papers)Lizhi Liu (1 shared paper)Jianye Liang (3 shared papers)Jiao Li (7 shared papers)
- Journals
- European Journal of Radiology (3 papers)Frontiers in Oncology (3 papers)European Radiology (3 papers)BMC Cancer (2 papers)IEEE Transactions on Consumer Electronics (1 paper)
- Partner nations
- ChinaUnited StatesNetherlands
In The Last Decade
Yaopan Wu
23 papers receiving 341 citations
Peers
Comparison fields: 5 of 40
- Radiology, Nuclear Medicine and Imaging 158
- Gastroenterology 30
- Health Informatics 4
- Otorhinolaryngology 10
- Cancer Research 32
Countries citing papers authored by Yaopan Wu
This map shows the geographic impact of Yaopan Wu'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 Yaopan Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yaopan Wu more than expected).
Fields of papers citing papers by Yaopan Wu
This network shows the impact of papers produced by Yaopan Wu. 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 Yaopan Wu. The network helps show where Yaopan Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Yaopan Wu, 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 39 | |
| 2 | 2015 | 36 | |
| 3 | 2020 | 32 | |
| 4 | 2013 | 24 | |
| 5 | 2018 | 23 | |
| 6 | 2012 | 21 | |
| 7 | 2020 | 20 | |
| 8 | 2019 | 19 | |
| 9 | 2021 | 18 | |
| 10 | 2020 | 16 | |
| 11 | 2021 | 16 | |
| 12 | 2023 | 14 | |
| 13 | 2019 | 12 | |
| 14 | 2017 | 11 | |
| 15 | 2023 | 11 | |
| 16 | 2015 | 9 | |
| 17 | 2021 | 8 | |
| 18 | 2022 | 7 | |
| 19 | 2014 | 6 | |
| 20 | 2021 | 6 |
About Yaopan Wu
Yaopan Wu is a scholar working on Radiology, Nuclear Medicine and Imaging, Cancer Research, Hepatology, Pulmonary and Respiratory Medicine and Gastroenterology, having authored 26 papers that have together received 353 indexed citations. Recurring topics across this work include MRI in cancer diagnosis (4 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Hepatocellular Carcinoma Treatment and Prognosis (2 papers), Digital Radiography and Breast Imaging (2 papers), Breast Cancer Treatment Studies (2 papers), AI in cancer detection (2 papers), Gene expression and cancer classification (1 paper) and Bioinformatics and Genomic Networks (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (158 citations), Gastroenterology (30 citations), Health Informatics (4 citations), Otorhinolaryngology (10 citations) and Cancer Research (32 citations). Yaopan Wu has collaborated with scholars based in China, United States and Netherlands. Frequent co-authors include Ni He, Li Li, Hongmin Cai, Peiqiang Cai, Jieting Chen, Lizhi Liu, Jianye Liang, Jiao Li, Chuan-miao Xie and Zhaoxiang Ye. Their work appears in journals such as European Journal of Radiology, Frontiers in Oncology, European Radiology, BMC Cancer and IEEE Transactions on Consumer Electronics.
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.