Wang Ya
Impact in
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- MRI in cancer diagnosis
- Advanced MRI Techniques and Applications
- Radiomics and Machine Learning in Medical Imaging
Papers in
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- Aortic aneurysm repair treatments 4
- Aortic Disease and Treatment Approaches 3
- Co-authors
- Xianquan Zhan (1 shared paper)Miaolong Lu (1 shared paper)William D. Rooney (2 shared papers)Charles S. Springer (2 shared papers)Luminita A. Tudorica (2 shared papers)Xin Li (2 shared papers)Venkatraman Seshan (2 shared papers)Wei Huang (2 shared papers)
- Journals
- International Journal of Molecular Sciences (3 papers)Proceedings of the National Academy of Sciences (2 papers)PLoS ONE (2 papers)Veterinary Sciences (1 paper)International Journal of Cardiology (1 paper)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Wang Ya
55 papers receiving 782 citations
Peers
Comparison fields: 5 of 109
- Developmental Neuroscience 28
- Radiology, Nuclear Medicine and Imaging 129
- Hepatology 36
- Cancer Research 66
- Immunology 91
Countries citing papers authored by Wang Ya
This map shows the geographic impact of Wang Ya'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 Wang Ya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wang Ya more than expected).
Fields of papers citing papers by Wang Ya
This network shows the impact of papers produced by Wang Ya. 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 Wang Ya. The network helps show where Wang Ya may publish in the future.
Co-authors
The 25 scholars most cited alongside Wang Ya, 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 60 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 74 | |
| 2 | 2008 | 70 | |
| 3 | 2019 | 60 | |
| 4 | 2008 | 59 | |
| 5 | 2012 | 55 | |
| 6 | 2018 | 41 | |
| 7 | 2018 | 40 | |
| 8 | 2020 | 39 | |
| 9 | 2016 | 29 | |
| 10 | 2021 | 22 | |
| 11 | 2014 | 21 | |
| 12 | 2022 | 20 | |
| 13 | 2018 | 18 | |
| 14 | 2016 | 18 | |
| 15 | 2020 | 17 | |
| 16 | 2017 | 14 | |
| 17 | 2014 | 13 | |
| 18 | 2023 | 12 | |
| 19 | 2017 | 12 | |
| 20 | 2017 | 12 |
About Wang Ya
Wang Ya is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, Epidemiology, Immunology and Surgery, having authored 60 papers that have together received 787 indexed citations. Recurring topics across this work include Cardiac, Anesthesia and Surgical Outcomes (4 papers), Liver Disease Diagnosis and Treatment (4 papers), Aortic aneurysm repair treatments (4 papers), Pharmacological Effects of Natural Compounds (4 papers), Microbial Metabolism and Applications (3 papers), Anesthesia and Neurotoxicity Research (3 papers), Aortic Disease and Treatment Approaches (3 papers) and Advanced MRI Techniques and Applications (3 papers). The work is most often cited by research in Developmental Neuroscience (28 citations), Radiology, Nuclear Medicine and Imaging (129 citations), Hepatology (36 citations), Cancer Research (66 citations) and Immunology (91 citations). Wang Ya has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Xianquan Zhan, Miaolong Lu, William D. Rooney, Charles S. Springer, Luminita A. Tudorica, Xin Li, Venkatraman Seshan, Wei Huang, Elizabeth A. Morris and Ian Tagge. Their work appears in journals such as International Journal of Molecular Sciences, Proceedings of the National Academy of Sciences, PLoS ONE, Veterinary Sciences and International Journal of Cardiology.
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.