Guangyao Wu
- Health Informatics top 1%
- Artificial Intelligence in Healthcare and Education 3
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- Radiomics and Machine Learning in Medical Imaging 12
- Medical Imaging Techniques and Applications 3
- COVID-19 diagnosis using AI 3
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- Lung Cancer Diagnosis and Treatment 8
- Medical Imaging and Pathology Studies 3
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- Advanced X-ray and CT Imaging 5
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- AI in cancer detection 2
- Co-authors
- Philippe LambinTurkey RefaeeAbdalla IbrahimHenry C. WoodruffSebastian SanduleanuSergey PrimakovJianlin WuArthur Jochems
- Cited by
- Health InformaticsRadiology, Nuclear Medicine and ImagingPulmonary and Respiratory Medicine
- Journals
- Radiology (2 papers)European Journal of Nuclear Medicine and Molecular Imaging (1 paper)Methods (1 paper)
- Partner nations
- NetherlandsChinaBelgium
In The Last Decade
Guangyao Wu
22 papers receiving 754 citations
Peers
Comparison fields: 5 of 77
- Health Informatics 92
- Radiology, Nuclear Medicine and Imaging 556
- Pulmonary and Respiratory Medicine 298
- Biomedical Engineering 191
- Microbiology 2
Countries citing papers authored by Guangyao Wu
This map shows the geographic impact of Guangyao 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 Guangyao Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guangyao Wu more than expected).
Fields of papers citing papers by Guangyao Wu
This network shows the impact of papers produced by Guangyao 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 Guangyao Wu. The network helps show where Guangyao Wu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Guangyao 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 | 2022 | 9 | |
| 3 | 2022 | 26 | |
| 4 | 2022 | 10 | |
| 5 | 2021 | 13 | |
| 6 | 2021 | 44 | |
| 7 | 2021 | 80 | |
| 8 | 2021 | 4 | |
| 9 | 2021 | 4 | |
| 10 | 2020 | 28 | |
| 11 | 2020 | 82 | |
| 12 | 2020 | 37 | |
| 13 | 2020 | 166 | |
| 14 | 2020 | 109 | |
| 15 | 2019 | 33 | |
| 16 | 2017 | 17 | |
| 17 | 2017 | 43 | |
| 18 | 2016 | 7 | |
| 19 | 2013 | 5 | |
| 20 | 2012 | 3 |
About Guangyao Wu
Guangyao Wu is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine, having authored 22 papers that have together received 766 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (12 papers), Lung Cancer Diagnosis and Treatment (8 papers), Advanced X-ray and CT Imaging (5 papers), Medical Imaging Techniques and Applications (3 papers), Artificial Intelligence in Healthcare and Education (3 papers), COVID-19 diagnosis using AI (3 papers), Medical Imaging and Pathology Studies (3 papers) and AI in cancer detection (2 papers). The work is most often cited by research in Health Informatics (92 citations), Radiology, Nuclear Medicine and Imaging (556 citations) and Pulmonary and Respiratory Medicine (298 citations). Guangyao Wu has collaborated with scholars based in Netherlands, China and Belgium. Frequent co-authors include Philippe Lambin, Turkey Refaee, Abdalla Ibrahim, Henry C. Woodruff, Sebastian Sanduleanu, Sergey Primakov, Jianlin Wu, Arthur Jochems, Chenggong Yan and Iva Halilaj. Their work appears in journals such as Radiology, European Journal of Nuclear Medicine and Molecular Imaging and Methods.
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.