Wang Hai-ya

533 citations
42 papers · 375 · h-index 11

Impact in

Papers in

Wang Hai-ya

39 papers receiving 367 citations

Peers

Wang Hai-ya
Comparison fields: 5 of 89
  • Nephrology 19
  • Cardiology and Cardiovascular Medicine 55
  • Endocrinology, Diabetes and Metabolism 36
  • Molecular Biology 132
  • Plant Science 68
Replace Shilong Huang with:
Shilong Huang China
Jia Wei China
Liu Miao China
Giuseppe Pennisi Italy
Yunqiang Zhang China
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Wang Hai-ya relative to Shilong Huang China Shilong Huang's profile →
Citations per field
00.5×4.5×
Shilong Huang · 1×
Citations per year

Countries citing papers authored by Wang Hai-ya

Since Specialization
Citations

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

Fields of papers citing papers by Wang Hai-ya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wang Hai-ya. 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 Wang Hai-ya. The network helps show where Wang Hai-ya may publish in the future.

Co-authors

The 25 scholars most cited alongside Wang Hai-ya, 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 Wang Hai-ya Line = papers co-authored together Wang Hai-ya links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201765
2 201245
3 201835
4 202030
5 200929
6 201119
7 201414
8 201114
9 201814
10 200914
11 202011
12 20158
13 20228
14
Community-based screening for chronic kidney disease among population older than 40 years in Beijing
20067
15 20207
16 20246
17
[Association between total antioxidant status and atherosclerosis in elderly patients with essential hypertension].
20136
18 20165
19
Comparative effects between Astragalus-Angelica mixture and enalapril on expression of connective tissue growth factor in rats with renal tubulointerstitial fibrosis
20034
20 20204

About Wang Hai-ya

Wang Hai-ya is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine, Physiology, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine, having authored 42 papers that have together received 375 indexed citations. Recurring topics across this work include Cardiovascular Health and Disease Prevention (4 papers), Cardiac Fibrosis and Remodeling (4 papers), Receptor Mechanisms and Signaling (3 papers), Nitric Oxide and Endothelin Effects (3 papers), Machine Fault Diagnosis Techniques (3 papers), Engineering Diagnostics and Reliability (3 papers), Angiogenesis and VEGF in Cancer (3 papers) and Signaling Pathways in Disease (2 papers). The work is most often cited by research in Nephrology (19 citations), Cardiology and Cardiovascular Medicine (55 citations), Endocrinology, Diabetes and Metabolism (36 citations), Molecular Biology (132 citations) and Plant Science (68 citations). Wang Hai-ya has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Ningyuan Fang, Pingjin Gao, Lu Guo, Yuting Gu, Eduardo Blumwald, Huimin Feng, Ling Yu, Jianliang Zhang, Guohua Xu and Qing X. Li. Their work appears in journals such as Gait & Posture, PLoS ONE, FEBS Letters, Meitan xuebao and Medicine.

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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