Ya‐Hui Wang

2.5k citations
88 papers · 1.7k · h-index 22

Impact in

Papers in

Ya‐Hui Wang

81 papers receiving 1.6k citations

Peers

Ya‐Hui Wang
Comparison fields: 5 of 150
  • Speech and Hearing 100
  • Infectious Diseases 211
  • Modeling and Simulation 54
  • Biochemistry 47
  • Nephrology 52
Replace Yoshio Hirota with:
Yoshio Hirota Japan
Zsolt Szakács Hungary
Wojciech Feleszko Poland
Rossella Cianci Italy
Lorenzo Berra United States
Ji Ye Jung South Korea
Chien‐Yu Lin Taiwan
Ki‐Suck Jung South Korea
Tse–Ling Fong United States
Marco Contoli Italy
Ya‐Hui Wang relative to Yoshio Hirota Japan Yoshio Hirota's profile →
Citations per field
00.5×3.5×
Yoshio Hirota · 1×
Citations per year

Countries citing papers authored by Ya‐Hui Wang

Since Specialization
Citations

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

Fields of papers citing papers by Ya‐Hui Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 88 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020272
2 2008106
3 2015101
4 200876
5 202060
6 202154
7 202054
8 202253
9 202250
10 201741
11 202240
12 200935
13 201833
14 201832
15 202226
16 201726
17 202025
18 202125
19 202225
20 201724

About Ya‐Hui Wang

Ya‐Hui Wang is a scholar working on Pulmonary and Respiratory Medicine, Surgery, Epidemiology, Infectious Diseases and Cardiology and Cardiovascular Medicine, having authored 88 papers that have together received 1.7k indexed citations. Recurring topics across this work include Chronic Obstructive Pulmonary Disease (COPD) Research (8 papers), COVID-19 Clinical Research Studies (5 papers), Osteoarthritis Treatment and Mechanisms (4 papers), Erythropoietin and Anemia Treatment (4 papers), Respiratory Support and Mechanisms (3 papers), Dysphagia Assessment and Management (3 papers), Voice and Speech Disorders (3 papers) and Obstructive Sleep Apnea Research (3 papers). The work is most often cited by research in Speech and Hearing (100 citations), Infectious Diseases (211 citations), Modeling and Simulation (54 citations), Biochemistry (47 citations) and Nephrology (52 citations). Ya‐Hui Wang has collaborated with scholars based in Taiwan, China and United States. Frequent co-authors include Chih‐Cheng Lai, Cheng‐Yi Wang, Po‐Ren Hsueh, Wen‐Chien Ko, Jiunn-Jong Wu, Huan-Yao Lei, Chao‐Hsien Chen, Likwang Chen, Hao‐Chien Wang and Yi-Wen Chen. Their work appears in journals such as PLoS ONE, Medicine, International Journal of COPD, Frontiers in Pharmacology and Journal of Clinical 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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