Dijia Wu
Impact in
- Health Informatics top 1%
- Artificial Intelligence in Healthcare and Education
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- COVID-19 diagnosis using AI
- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis
Papers in
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- Cardiac Imaging and Diagnostics 6
- Medical Imaging Techniques and Applications 5
- Radiomics and Machine Learning in Medical Imaging 5
- COVID-19 diagnosis using AI 4
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- Advanced X-ray and CT Imaging 6
- Medical Imaging and Analysis 4
- Co-authors
- Dinggang Shen (8 shared papers)Feng Shi (4 shared papers)Huan Yuan (3 shared papers)Liming Xia (3 shared papers)Fuhua Yan (3 shared papers)He Sui (2 shared papers)Bin Song (2 shared papers)Ying Wei (2 shared papers)
- Journals
- IEEE Transactions on Medical Imaging (4 papers)European Radiology (3 papers)Radiology (2 papers)La radiologia medica (2 papers)Nature Communications (1 paper)
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Dijia Wu
25 papers receiving 982 citations
Dijia Wu's Hit Papers
Peers
Comparison fields: 5 of 99
- Health Informatics 144
- Radiology, Nuclear Medicine and Imaging 752
- Hepatology 127
- Artificial Intelligence 354
- Computer Vision and Pattern Recognition 129
Countries citing papers authored by Dijia Wu
This map shows the geographic impact of Dijia 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 Dijia Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dijia Wu more than expected).
Fields of papers citing papers by Dijia Wu
This network shows the impact of papers produced by Dijia 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 Dijia Wu. The network helps show where Dijia Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Dijia 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 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 264 | |
| 2 | 2020 | 172 | |
| 3 | 2020 | 165 | |
| 4 | Multi-scale and multi-parametric radiomics of gadoxetate disodium–enhanced MRI predicts microvascular invasion and outcome in patients with solitary hepatocellular carcinoma ≤ 5 cm Hit paper breakdown → | 2021 | 152 |
| 5 | 2010 | 47 | |
| 6 | 2014 | 22 | |
| 7 | 2022 | 20 | |
| 8 | 2023 | 18 | |
| 9 | 2022 | 18 | |
| 10 | 2022 | 18 | |
| 11 | 2022 | 17 | |
| 12 | 2023 | 16 | |
| 13 | 2020 | 13 | |
| 14 | 2015 | 11 | |
| 15 | 2021 | 9 | |
| 16 | 2009 | 7 | |
| 17 | 2008 | 7 | |
| 18 | 2024 | 6 | |
| 19 | 2011 | 5 | |
| 20 | 2021 | 5 |
About Dijia Wu
Dijia Wu is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering, Computer Vision and Pattern Recognition, Surgery and Pulmonary and Respiratory Medicine, having authored 28 papers that have together received 1.0k indexed citations. Recurring topics across this work include Advanced X-ray and CT Imaging (6 papers), Cardiac Imaging and Diagnostics (6 papers), Medical Imaging Techniques and Applications (5 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), COVID-19 diagnosis using AI (4 papers), Medical Imaging and Analysis (4 papers), Medical Image Segmentation Techniques (3 papers) and Hepatocellular Carcinoma Treatment and Prognosis (2 papers). The work is most often cited by research in Health Informatics (144 citations), Radiology, Nuclear Medicine and Imaging (752 citations), Hepatology (127 citations), Artificial Intelligence (354 citations) and Computer Vision and Pattern Recognition (129 citations). Dijia Wu has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Dinggang Shen, Feng Shi, Huan Yuan, Liming Xia, Fuhua Yan, He Sui, Bin Song, Ying Wei, Fei Shan and Yaozong Gao. Their work appears in journals such as IEEE Transactions on Medical Imaging, European Radiology, Radiology, La radiologia medica and Nature Communications.
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.