Yun Liu
Impact in
- Health Informatics top 0.05%
- Artificial Intelligence in Healthcare and Education
-
- Radiomics and Machine Learning in Medical Imaging
- Retinal Imaging and Analysis
- COVID-19 diagnosis using AI
Papers in
-
- Artificial Intelligence in Healthcare and Education 10
-
- Retinal Imaging and Analysis 19
- Radiomics and Machine Learning in Medical Imaging 12
- Co-authors
- Lily PengPo-Hsuan Cameron ChenGreg S. CorradoDale R. WebsterAvinash V. VaradarajanMichael V. McConnellKaty BlumerRyan Poplin
- Journals
- Nature Biomedical Engineering (4 papers)npj Digital Medicine (3 papers)The Lancet Digital Health (3 papers)PLoS ONE (3 papers)JAMA Network Open (2 papers)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Yun Liu
100 papers receiving 5.2k citations
Hit Papers
Peers
Comparison fields: 5 of 191
- Health Informatics 877
- Radiology, Nuclear Medicine and Imaging 2.4k
- Ophthalmology 719
- Health Information Management 345
- Artificial Intelligence 2.0k
Countries citing papers authored by Yun Liu
This map shows the geographic impact of Yun Liu'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 Yun Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yun Liu more than expected).
Fields of papers citing papers by Yun Liu
This network shows the impact of papers produced by Yun Liu. 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 Yun Liu. The network helps show where Yun Liu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yun Liu, 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 | 2025 | 2 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 6 | |
| 4 | 2024 | 5 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 12 | |
| 7 | 2024 | 25 | |
| 8 | 2024 | 2 | |
| 9 | 2024 | 0 | |
| 10 | 2023 | 0 | |
| 11 | 2023 | 12 | |
| 12 | 2023 | 20 | |
| 13 | 2023 | 6 | |
| 14 | 2023 | 10 | |
| 15 | 2022 | 30 | |
| 16 | Velocity field and coherent structures in the near wake of a utility-scale wind turbine | 2017 | 1 |
| 17 | 2014 | 6 | |
| 18 | Score Entry and Statistical Analysis Based on the Excel Platform | 2011 | 1 |
| 19 | A Review of Chinese Vocabulary Statistic Studies | 2009 | 1 |
| 20 | Study of the histology in sex changing from intersex to male of Monopterus albus (Zuiew) | 1995 | 17 |
About Yun Liu
Yun Liu is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging, Ophthalmology, Artificial Intelligence and Health Information Management, having authored 112 papers that have together received 5.4k indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (19 papers), AI in cancer detection (13 papers), Radiomics and Machine Learning in Medical Imaging (12 papers), Retinal Diseases and Treatments (10 papers), Artificial Intelligence in Healthcare and Education (10 papers), Colorectal Cancer Screening and Detection (6 papers), Acute Ischemic Stroke Management (6 papers) and Topic Modeling (5 papers). The work is most often cited by research in Health Informatics (877 citations), Radiology, Nuclear Medicine and Imaging (2.4k citations), Ophthalmology (719 citations), Health Information Management (345 citations) and Artificial Intelligence (2.0k citations). Yun Liu has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Lily Peng, Po-Hsuan Cameron Chen, Greg S. Corrado, Dale R. Webster, Avinash V. Varadarajan, Michael V. McConnell, Katy Blumer, Ryan Poplin, Martin C. Stumpe and Jason Hipp. Their work appears in journals such as Nature Biomedical Engineering, npj Digital Medicine, The Lancet Digital Health, PLoS ONE and JAMA Network Open.
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.