Weilan Wu

516 citations
9 papers · 387 · h-index 7

Impact in

Papers in

Weilan Wu

9 papers receiving 381 citations

Peers

Weilan Wu
Comparison fields: 5 of 62
  • Radiology, Nuclear Medicine and Imaging 232
  • Health Informatics 11
  • Pulmonary and Respiratory Medicine 234
  • Cancer Research 52
  • Internal Medicine 9
Replace Giovanna Sartor with:
Giovanna Sartor Italy
Beibei Jiang China
Domiziana Santucci Italy
David J. Noble United Kingdom
Renata Zelić Sweden
Xinhua Ye China
Giacomo Feliciani Italy
Byong Yong Yi United States
Zixuan Cheng China
M. Lobbes Netherlands
Weilan Wu relative to Giovanna Sartor Italy Giovanna Sartor's profile →
Citations per field
00.5×4.5×
Giovanna Sartor · 1×
Citations per year

Countries citing papers authored by Weilan Wu

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Weilan Wu Line = papers co-authored together Weilan Wu links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1 2018161
2 202098
3 201963
4 201330
5 201614
6 201911
7 20126
8 20193
9
[Effects of high and low shear stress on vascular remodeling and endothelial vascular cell adhesion molecular-1 expression in mouse abdominal aorta].
20111

About Weilan Wu

Weilan Wu is a scholar working on Pulmonary and Respiratory Medicine, Molecular Biology, Radiology, Nuclear Medicine and Imaging, Cancer Research and Cardiology and Cardiovascular Medicine, having authored 9 papers that have together received 387 indexed citations. Recurring topics across this work include Lung Cancer Diagnosis and Treatment (2 papers), Photoacoustic and Ultrasonic Imaging (2 papers), Protease and Inhibitor Mechanisms (2 papers), Venous Thromboembolism Diagnosis and Management (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Aortic aneurysm repair treatments (2 papers), Angiogenesis and VEGF in Cancer (1 paper) and Ultrasound and Hyperthermia Applications (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (232 citations), Health Informatics (11 citations), Pulmonary and Respiratory Medicine (234 citations), Cancer Research (52 citations) and Internal Medicine (9 citations). Weilan Wu has collaborated with scholars based in China. Frequent co-authors include Ming Li, Wei Zhao, Yingli Sun, Liang Jin, Yanqing Hua, Bingbing Ni, Peijun Wang, Cheng Li, Zhiming Yang and Pan Gao. Their work appears in journals such as Molecular Imaging and Biology, Investigative Radiology, Journal of Molecular and Cellular Cardiology, International Journal of Cardiology and Thrombosis and Haemostasis.

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.

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