Hongyan Wu

989 total citations · 1 hit paper
24 papers, 665 citations indexed

About

Hongyan Wu is a scholar working on Economics and Econometrics, General Health Professions and Artificial Intelligence. According to data from OpenAlex, Hongyan Wu has authored 24 papers receiving a total of 665 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Economics and Econometrics, 6 papers in General Health Professions and 3 papers in Artificial Intelligence. Recurrent topics in Hongyan Wu's work include Health Systems, Economic Evaluations, Quality of Life (7 papers), Global Health Care Issues (4 papers) and Economic and Environmental Valuation (3 papers). Hongyan Wu is often cited by papers focused on Health Systems, Economic Evaluations, Quality of Life (7 papers), Global Health Care Issues (4 papers) and Economic and Environmental Valuation (3 papers). Hongyan Wu collaborates with scholars based in China, United States and Malaysia. Hongyan Wu's co-authors include Gordon G. Liu, Minghui Li, Nan Luo, Geoffrey R. Martin, Yan Xiao, Ghazanfar Ali Abbasi, Noor Fareen Abdul Rahim, Mohammad Iranmanesh, Xiaoning He and Sibo Zheng and has published in prestigious journals such as The Journals of Gerontology Series A, Journal of High Energy Physics and Frontiers in Psychology.

In The Last Decade

Hongyan Wu

22 papers receiving 643 citations

Hit Papers

Chinese Time Trade-Off Values for EQ-5D Health States 2014 2026 2018 2022 2014 50 100 150 200 250

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Hongyan Wu China 12 237 140 104 79 78 24 665
William Morrison United Kingdom 18 142 0.6× 61 0.4× 95 0.9× 16 0.2× 13 0.2× 56 1.3k
Denis Fischbacher‐Smith United Kingdom 12 80 0.3× 102 0.7× 124 1.2× 6 0.1× 16 0.2× 43 571
Rajesh Sharma India 19 151 0.6× 174 1.2× 42 0.4× 9 0.1× 9 0.1× 85 1.5k
Roselaine Ruviaro Zanini Brazil 14 41 0.2× 94 0.7× 26 0.3× 10 0.1× 9 0.1× 54 518
M L Senior United Kingdom 16 211 0.9× 160 1.1× 95 0.9× 99 1.3× 4 0.1× 32 693
Marta Marsilio Italy 14 111 0.5× 139 1.0× 49 0.5× 20 0.3× 4 0.1× 49 568
Kathrin Damm Germany 14 132 0.6× 223 1.6× 135 1.3× 13 0.2× 3 0.0× 41 746
Andrea H. Okun United States 20 46 0.2× 130 0.9× 68 0.7× 25 0.3× 4 0.1× 34 1.6k
H. S. Kuo Taiwan 14 51 0.2× 101 0.7× 67 0.6× 7 0.1× 8 0.1× 19 789
Penelope M. Mullen United Kingdom 8 143 0.6× 153 1.1× 206 2.0× 23 0.3× 8 0.1× 18 635

Countries citing papers authored by Hongyan Wu

Since Specialization
Citations

This map shows the geographic impact of Hongyan 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 Hongyan Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hongyan Wu more than expected).

Fields of papers citing papers by Hongyan Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hongyan 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 Hongyan Wu. The network helps show where Hongyan Wu may publish in the future.

Co-authorship network of co-authors of Hongyan Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Hongyan Wu. A scholar is included among the top collaborators of Hongyan Wu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hongyan Wu. Hongyan Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wu, Hongyan, et al.. (2025). AI-Driven Risk Control for Health Insurance Fund Management: A Data-Driven Approach. International Journal of Computers Communications & Control. 20(2). 1 indexed citations
2.
Yang, Wentao, et al.. (2024). Privacy-Preserving Federated Learning with Homomorphic Encryption and Sparse Compression. 192–198. 1 indexed citations
3.
Bai, Yang, et al.. (2024). Backdoor Attack and Defense on Deep Learning: A Survey. IEEE Transactions on Computational Social Systems. 12(1). 404–434. 3 indexed citations
4.
Wu, Hongyan, Zhihao Yang, Yan Huang, et al.. (2024). Testing four cognition bolt-on items to the EQ-5D in a general Chinese population. The European Journal of Health Economics. 26(3). 403–411. 2 indexed citations
5.
Abbasi, Ghazanfar Ali, et al.. (2022). Determinants of SME’s Social Media Marketing Adoption: Competitive Industry as a Moderator. SAGE Open. 12(1). 77 indexed citations
7.
Liu, Gordon G., Haijing Guan, Xuejing Jin, et al.. (2022). Rural population’s preferences matter: a value set for the EQ-5D-3L health states for China’s rural population. Health and Quality of Life Outcomes. 20(1). 14–14. 14 indexed citations
8.
Wu, Jing, Shitong Xie, Xiaoning He, et al.. (2021). Valuation of SF-6Dv2 Health States in China Using Time Trade-off and Discrete-Choice Experiment with a Duration Dimension. PharmacoEconomics. 39(5). 521–535. 49 indexed citations
9.
Wu, Hongyan, et al.. (2021). Non-Operative Shoulder Dysfunction in the United States Military. Military Medicine. 188(5-6). e1003–e1009. 3 indexed citations
10.
Wu, Hongyan, et al.. (2021). Assessing the reliability and validity of the ICECAP-A instrument in Chinese type 2 diabetes patients. Health and Quality of Life Outcomes. 19(1). 5–5. 4 indexed citations
11.
Yang, Fan, Shan Jiang, Xiaoning He, et al.. (2020). Do Rural Residents in China Understand EQ-5D-5L as Intended? Evidence From a Qualitative Study. PharmacoEconomics - Open. 5(1). 101–109. 25 indexed citations
12.
Hu, Ruying, et al.. (2018). [Estimation on the health life expectancy of adults in Zhejiang province, 2016].. PubMed. 39(9). 1249–1254.
13.
Tang, Chengxiang, et al.. (2018). Adaptation and assessments of the Chinese version of the ICECAP-A measurement. Health and Quality of Life Outcomes. 16(1). 45–45. 26 indexed citations
14.
Wu, Hongyan. (2015). Quality Analysis of Pharmacoeconomics Evaluation and Application Literature in China During 2009-2013. Value in Health. 18(7). A553–A553. 1 indexed citations
15.
Wu, Hongyan, et al.. (2015). Adoption of Social Media in the Australian Energy and Resources Sectors. UCL Discovery (University College London). 1 indexed citations
16.
Liu, Gordon G., et al.. (2014). Chinese Time Trade-Off Values for EQ-5D Health States. Value in Health. 17(5). 597–604. 255 indexed citations breakdown →
17.
Liu, Ru, et al.. (2014). Applying the fuzzy SERVQUAL method to measure the service quality in certification & inspection industry. Applied Soft Computing. 26. 508–512. 46 indexed citations
18.
Wu, Hongyan, et al.. (2013). Payment reform and changes in health care in China. Value in Health. 16(3). A199–A199. 3 indexed citations
19.
Wu, Hongyan, Chi‐Ho Lee, & Matthew M. Rechler. (1999). Proteolysis of Insulin-Like Growth Factor Binding Protein-3 in Serum from Pregnant, Non-Pregnant and Fetal Rats by Matrix Metalloproteinases and Serine Proteases. Hormone and Metabolic Research. 31(02/03). 186–191. 20 indexed citations
20.
Lee, Christopher, et al.. (1999). The Absence of 150-kDa Insulin-Like Growth Factor Complexes in Fetal Rat Serum is not Due to a Lack of Functional Acid-Labile Subunit. Hormone and Metabolic Research. 31(02/03). 182–185. 5 indexed citations

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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