Qingxia Wu
Impact in
- Health Informatics top 1%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
- MRI in cancer diagnosis
Papers in
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- Radiomics and Machine Learning in Medical Imaging 21
- MRI in cancer diagnosis 11
- COVID-19 diagnosis using AI 4
- Medical Imaging Techniques and Applications 4
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- Endometrial and Cervical Cancer Treatments 10
- Co-authors
- Meiyun Wang (12 shared papers)Shuo Wang (5 shared papers)Yunfei Zha (3 shared papers)Jie Tian (6 shared papers)Xiaoming Qiu (2 shared papers)Meiyun Wang (7 shared papers)Liusu Wang (3 shared papers)Yan Bai (4 shared papers)
- Journals
- Theranostics (2 papers)European Radiology (2 papers)Frontiers in Oncology (2 papers)European Journal of Radiology (2 papers)International Journal of Gynecological Cancer (1 paper)
- Partner nations
- ChinaUnited StatesIndia
In The Last Decade
Qingxia Wu
38 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 110
- Health Informatics 119
- Radiology, Nuclear Medicine and Imaging 709
- Obstetrics and Gynecology 191
- Cancer Research 136
- Artificial Intelligence 218
Countries citing papers authored by Qingxia Wu
This map shows the geographic impact of Qingxia 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 Qingxia Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qingxia Wu more than expected).
Fields of papers citing papers by Qingxia Wu
This network shows the impact of papers produced by Qingxia 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 Qingxia Wu. The network helps show where Qingxia Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Qingxia 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 42 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 339 | |
| 2 | 2017 | 104 | |
| 3 | 2019 | 85 | |
| 4 | 2023 | 78 | |
| 5 | 2020 | 73 | |
| 6 | 2020 | 67 | |
| 7 | 2018 | 58 | |
| 8 | 2019 | 48 | |
| 9 | 2021 | 40 | |
| 10 | 2011 | 29 | |
| 11 | 2017 | 29 | |
| 12 | 2018 | 26 | |
| 13 | 2017 | 22 | |
| 14 | 2022 | 20 | |
| 15 | 2021 | 15 | |
| 16 | 2024 | 13 | |
| 17 | 2024 | 10 | |
| 18 | 2024 | 10 | |
| 19 | 2024 | 9 | |
| 20 | 2017 | 9 |
About Qingxia Wu
Qingxia Wu is a scholar working on Radiology, Nuclear Medicine and Imaging, Obstetrics and Gynecology, Biomedical Engineering, Epidemiology and Hepatology, having authored 42 papers that have together received 1.1k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (21 papers), MRI in cancer diagnosis (11 papers), Endometrial and Cervical Cancer Treatments (10 papers), Hepatocellular Carcinoma Treatment and Prognosis (6 papers), COVID-19 diagnosis using AI (4 papers), Advanced X-ray and CT Imaging (4 papers), Medical Imaging Techniques and Applications (4 papers) and AI in cancer detection (4 papers). The work is most often cited by research in Health Informatics (119 citations), Radiology, Nuclear Medicine and Imaging (709 citations), Obstetrics and Gynecology (191 citations), Cancer Research (136 citations) and Artificial Intelligence (218 citations). Qingxia Wu has collaborated with scholars based in China, United States and India. Frequent co-authors include Meiyun Wang, Shuo Wang, Yunfei Zha, Jie Tian, Xiaoming Qiu, Meiyun Wang, Liusu Wang, Yan Bai, Yongbei Zhu and Meng Niu. Their work appears in journals such as Theranostics, European Radiology, Frontiers in Oncology, European Journal of Radiology and International Journal of Gynecological Cancer.
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.