Weilan Wu
Impact in
-
- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
-
- Lung Cancer Diagnosis and Treatment 2
- Aortic aneurysm repair treatments 1
- Vasculitis and related conditions 1
-
- Ultrasound and Hyperthermia Applications 2
- Co-authors
- Liang Jin (2 shared papers)Ming Li (3 shared papers)Wei Zhao (2 shared papers)Yingli Sun (2 shared papers)Cheng Li (1 shared paper)Bingbing Ni (1 shared paper)Zhiming Yang (1 shared paper)Jiancheng Yang (1 shared paper)
- Journals
- Thrombosis and Haemostasis (1 paper)Journal of Molecular and Cellular Cardiology (1 paper)Investigative Radiology (1 paper)Molecular Imaging and Biology (1 paper)European Radiology (1 paper)
- Partner nations
- China
In The Last Decade
Weilan Wu
9 papers receiving 392 citations
Peers
Comparison fields: 5 of 56
- Radiology, Nuclear Medicine and Imaging 143
- Health Informatics 9
- Pulmonary and Respiratory Medicine 166
- Cancer Research 46
- Internal Medicine 6
Countries citing papers authored by Weilan Wu
This map shows the geographic impact of Weilan 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 Weilan Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weilan Wu more than expected).
Fields of papers citing papers by Weilan Wu
This network shows the impact of papers produced by Weilan 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 Weilan Wu. The network helps show where Weilan Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Weilan 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 | 2018 | 166 | |
| 2 | 2020 | 103 | |
| 3 | 2019 | 63 | |
| 4 | 2013 | 31 | |
| 5 | 2016 | 14 | |
| 6 | 2019 | 11 | |
| 7 | 2012 | 6 | |
| 8 | 2019 | 3 | |
| 9 | [Effects of high and low shear stress on vascular remodeling and endothelial vascular cell adhesion molecular-1 expression in mouse abdominal aorta]. | 2011 | 1 |
About Weilan Wu
Weilan Wu is a scholar working on Pulmonary and Respiratory Medicine, Biomedical Engineering, Molecular Biology, Ophthalmology and Artificial Intelligence, having authored 9 papers that have together received 398 indexed citations. Recurring topics across this work include Lung Cancer Diagnosis and Treatment (2 papers), Ultrasound and Hyperthermia Applications (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Ocular Diseases and Behçet’s Syndrome (1 paper), Systemic Lupus Erythematosus Research (1 paper), Aortic aneurysm repair treatments (1 paper), Vasculitis and related conditions (1 paper) and AI in cancer detection (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (143 citations), Health Informatics (9 citations), Pulmonary and Respiratory Medicine (166 citations), Cancer Research (46 citations) and Internal Medicine (6 citations). Weilan Wu has collaborated with scholars based in China. Frequent co-authors include Liang Jin, Ming Li, Wei Zhao, Yingli Sun, Cheng Li, Bingbing Ni, Zhiming Yang, Jiancheng Yang, Peijun Wang and Pan Gao. Their work appears in journals such as Thrombosis and Haemostasis, Journal of Molecular and Cellular Cardiology, Investigative Radiology, Molecular Imaging and Biology and European Radiology.
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.