Lanping Wu
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
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- Medical Research and Treatments
- Traditional Chinese Medicine Analysis
Papers in
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- Artificial Intelligence in Healthcare and Education 3
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- Congenital Heart Disease Studies 8
- Co-authors
- Yuqi Zhang (6 shared papers)Mei‐Rong Huang (2 shared papers)Jingli Hou (1 shared paper)Yumin Zhong (2 shared papers)Yanjun Pan (1 shared paper)Qiang Zhao (1 shared paper)Deling Kong (1 shared paper)Hao Tian (1 shared paper)
- Journals
- Frontiers in Pediatrics (2 papers)Heart and Vessels (1 paper)Nature Communications (1 paper)European Journal of Pediatrics (1 paper)International journal of cardiac imaging (1 paper)
- Partner nations
- ChinaUnited States
In The Last Decade
Lanping Wu
15 papers receiving 330 citations
Peers
Comparison fields: 5 of 53
- Health Informatics 22
- Complementary and alternative medicine 55
- Cardiology and Cardiovascular Medicine 86
- Molecular Medicine 14
- Biomaterials 23
Countries citing papers authored by Lanping Wu
This map shows the geographic impact of Lanping 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 Lanping Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lanping Wu more than expected).
Fields of papers citing papers by Lanping Wu
This network shows the impact of papers produced by Lanping 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 Lanping Wu. The network helps show where Lanping Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Lanping 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 | 2021 | 108 | |
| 2 | 2020 | 74 | |
| 3 | 2017 | 58 | |
| 4 | 2022 | 19 | |
| 5 | 2014 | 18 | |
| 6 | 2022 | 11 | |
| 7 | 2010 | 9 | |
| 8 | 2012 | 8 | |
| 9 | 2019 | 8 | |
| 10 | 2020 | 8 | |
| 11 | 2017 | 5 | |
| 12 | 2022 | 5 | |
| 13 | [Automatic search for the best cross-sections of the three-dimensional ultrasound image of heart by template matching]. | 2008 | 3 |
| 14 | 2025 | 2 | |
| 15 | 2023 | 1 | |
| 16 | 2026 | 0 |
About Lanping Wu
Lanping Wu is a scholar working on Health Informatics, Epidemiology, Cardiology and Cardiovascular Medicine, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging, having authored 16 papers that have together received 337 indexed citations. Recurring topics across this work include Congenital Heart Disease Studies (8 papers), Medical Image Segmentation Techniques (3 papers), Artificial Intelligence in Healthcare and Education (3 papers), Cardiovascular Function and Risk Factors (3 papers), Cardiac Imaging and Diagnostics (2 papers), Cardiac electrophysiology and arrhythmias (2 papers), Cardiac Ischemia and Reperfusion (1 paper) and COVID-19 Clinical Research Studies (1 paper). The work is most often cited by research in Health Informatics (22 citations), Complementary and alternative medicine (55 citations), Cardiology and Cardiovascular Medicine (86 citations), Molecular Medicine (14 citations) and Biomaterials (23 citations). Lanping Wu has collaborated with scholars based in China and United States. Frequent co-authors include Yuqi Zhang, Mei‐Rong Huang, Jingli Hou, Yumin Zhong, Yanjun Pan, Qiang Zhao, Deling Kong, Hao Tian, Jie Shen and He Wang. Their work appears in journals such as Frontiers in Pediatrics, Heart and Vessels, Nature Communications, European Journal of Pediatrics and International journal of cardiac imaging.
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.