Cheng‐Kang Wang

23 papers receiving 310 citations

Peers

Cheng‐Kang Wang
Comparison fields: 5 of 71
  • Infectious Diseases 95
  • Statistics, Probability and Uncertainty 27
  • Signal Processing 32
  • Endocrinology, Diabetes and Metabolism 40
  • Health Informatics 3
Replace Satoshi Hara with:
Satoshi Hara Japan
Shih‐Ming Huang Taiwan
Wenhui Lei China
Robert Herring United States
Rajesh Thomas India
Arindam Kar United Kingdom
Vineet Agarwal United States
Xiaomo Wang China
Jiamin Liu China
Cheng‐Kang Wang relative to Satoshi Hara Japan Satoshi Hara's profile →
Citations per field
00.5×
Satoshi Hara · 1×
Citations per year

Countries citing papers authored by Cheng‐Kang Wang

Since Specialization
Citations

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

Fields of papers citing papers by Cheng‐Kang Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cheng‐Kang 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 Cheng‐Kang Wang. The network helps show where Cheng‐Kang Wang may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008113
2 201730
3 200921
4 202218
5 201918
6 201916
7 202216
8 202314
9 202213
10 202211
11 20099
12 20235
13 20215
14 20085
15 20245
16 20243
17 20253
18 20083
19 20232
20 20232

About Cheng‐Kang Wang

Cheng‐Kang Wang is a scholar working on Endocrinology, Diabetes and Metabolism, Surgery, Signal Processing, Molecular Biology and Nephrology, having authored 27 papers that have together received 315 indexed citations. Recurring topics across this work include Thyroid Cancer Diagnosis and Treatment (7 papers), Thyroid and Parathyroid Surgery (4 papers), Speech and Audio Processing (4 papers), Advanced Adaptive Filtering Techniques (3 papers), Parathyroid Disorders and Treatments (3 papers), Histone Deacetylase Inhibitors Research (2 papers), Balance, Gait, and Falls Prevention (2 papers) and Head and Neck Anomalies (2 papers). The work is most often cited by research in Infectious Diseases (95 citations), Statistics, Probability and Uncertainty (27 citations), Signal Processing (32 citations), Endocrinology, Diabetes and Metabolism (40 citations) and Health Informatics (3 citations). Cheng‐Kang Wang has collaborated with scholars based in Taiwan, China and South Korea. Frequent co-authors include Ming‐Shyan Huang, Inn‐Wen Chong, Juey‐Jen Hwang, Chih‐Jen Yang, Wei‐Che Lin, Pi‐Ling Chiang, Jwu‐Sheng Hu, Yueh‐Sheng Chen, Hsiu-Ling Chen and Meng‐Hsiang Chen. Their work appears in journals such as International Journal of Hyperthermia, International Journal of Environmental Research and Public Health, Journal of Personalized Medicine, International Immunopharmacology and Cancer 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.

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