Mei-Chun Wang

29 papers receiving 358 citations

Peers

Mei-Chun Wang
Comparison fields: 5 of 88
  • Energy Engineering and Power Technology 27
  • Catalysis 39
  • Endocrinology, Diabetes and Metabolism 62
  • Modeling and Simulation 16
  • Ophthalmology 21
Replace N. Okada with:
N. Okada Japan
Yixue Yang China
Norihiro Kodama Japan
Fei She China
M Yano Japan
Sin Young Kim South Korea
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Citations per year

Countries citing papers authored by Mei-Chun Wang

Since Specialization
Citations

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

Fields of papers citing papers by Mei-Chun Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201265
2 201737
3 201935
4 200824
5 200324
6
Hyperthyroidism is associated with higher plasma endothelin-1 concentrations.
200623
7 201119
8
The effects of different doses of atorvastatin on plasma endothelin-1 levels in type 2 diabetic patients with dyslipidemia.
200616
9 201115
10 200413
11 202212
12
Sclerotherapy of thyroid cystic nodules.
200311
13 201810
14 20228
15 20098
16 20206
17 19985
18 20205
19 20074
20 20214

About Mei-Chun Wang

Mei-Chun Wang is a scholar working on Endocrinology, Diabetes and Metabolism, Surgery, Molecular Biology, Numerical Analysis and Genetics, having authored 30 papers that have together received 364 indexed citations. Recurring topics across this work include Thyroid Disorders and Treatments (4 papers), Nitric Oxide and Endothelin Effects (3 papers), Fractional Differential Equations Solutions (3 papers), Hemoglobinopathies and Related Disorders (3 papers), Regulation of Appetite and Obesity (3 papers), Diabetes Management and Research (2 papers), Iterative Methods for Nonlinear Equations (2 papers) and Hormonal Regulation and Hypertension (2 papers). The work is most often cited by research in Energy Engineering and Power Technology (27 citations), Catalysis (39 citations), Endocrinology, Diabetes and Metabolism (62 citations), Modeling and Simulation (16 citations) and Ophthalmology (21 citations). Mei-Chun Wang has collaborated with scholars based in Taiwan, China and Macao. Frequent co-authors include Hing‐Chung Lam, Jenn‐Kuen Lee, Chih-Hsun Chu, Min Zhu, Liuzhang Ouyang, Chenghong Peng, Huaiyu Shao, Tsung‐I Hsu, Yu-Min Yeh and Shih‐Ting Huang. Their work appears in journals such as Journal of Cardiovascular Pharmacology, International Journal of Environmental Research and Public Health, Wireless Communications and Mobile Computing, Molecular Pharmacology and Current Vascular Pharmacology.

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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