Yaping Wu
Impact in
- Hematology top 2%
- Platelet Disorders and Treatments
- Blood groups and transfusion
- Clinical Biochemistry top 2%
- Advanced Glycation End Products research
Papers in
-
- Radiomics and Machine Learning in Medical Imaging 36
- Medical Imaging Techniques and Applications 35
- MRI in cancer diagnosis 13
- Advanced MRI Techniques and Applications 13
- Hematology 12
- Platelet Disorders and Treatments 10
- Co-authors
- Philip G. de GrootJan J. SixmaMeiyun WangMartijn F.B.G. GebbinkOnno KranenburgLoes M. J. Kroon-BatenburgBarend BoumaEmile E. Voest
- Journals
- European Journal of Nuclear Medicine and Molecular Imaging (8 papers)Blood (5 papers)Medical Physics (3 papers)Arteriosclerosis Thrombosis and Vascular Biology (3 papers)EJNMMI Physics (3 papers)
- Partner nations
- ChinaUnited StatesNetherlands
In The Last Decade
Yaping Wu
89 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 129
- Hematology 430
- Clinical Biochemistry 190
- Radiology, Nuclear Medicine and Imaging 567
- Immunology and Allergy 75
- Health Informatics 16
Countries citing papers authored by Yaping Wu
This map shows the geographic impact of Yaping 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 Yaping Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yaping Wu more than expected).
Fields of papers citing papers by Yaping Wu
This network shows the impact of papers produced by Yaping 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 Yaping Wu. The network helps show where Yaping Wu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yaping 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
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 4 | |
| 4 | 2024 | 10 | |
| 5 | 2024 | 6 | |
| 6 | 2024 | 5 | |
| 7 | 2024 | 2 | |
| 8 | 2024 | 3 | |
| 9 | 2024 | 9 | |
| 10 | 2024 | 1 | |
| 11 | 2023 | 11 | |
| 12 | 2023 | 0 | |
| 13 | 2023 | 20 | |
| 14 | 2023 | 15 | |
| 15 | 2023 | 7 | |
| 16 | 2022 | 43 | |
| 17 | 2022 | 8 | |
| 18 | 2021 | 2 | |
| 19 | 2020 | 49 | |
| 20 | 2002 | 94 |
About Yaping Wu
Yaping Wu is a scholar working on Radiology, Nuclear Medicine and Imaging, Hematology, Health Informatics, Neurology and Computer Vision and Pattern Recognition, having authored 102 papers that have together received 1.9k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (36 papers), Medical Imaging Techniques and Applications (35 papers), MRI in cancer diagnosis (13 papers), Advanced MRI Techniques and Applications (13 papers), Advanced X-ray and CT Imaging (13 papers), Platelet Disorders and Treatments (10 papers), Medical Image Segmentation Techniques (9 papers) and Brain Tumor Detection and Classification (6 papers). The work is most often cited by research in Hematology (430 citations), Clinical Biochemistry (190 citations), Radiology, Nuclear Medicine and Imaging (567 citations), Immunology and Allergy (75 citations) and Health Informatics (16 citations). Yaping Wu has collaborated with scholars based in China, United States and Netherlands. Frequent co-authors include Philip G. de Groot, Jan J. Sixma, Meiyun Wang, Martijn F.B.G. Gebbink, Onno Kranenburg, Loes M. J. Kroon-Batenburg, Barend Bouma, Emile E. Voest, Martin J. W. IJsseldijk and Yusong Lin. Their work appears in journals such as European Journal of Nuclear Medicine and Molecular Imaging, Blood, Medical Physics, Arteriosclerosis Thrombosis and Vascular Biology and EJNMMI Physics.
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.