Shih‐Bin Su
Impact in
- Sensory Systems top 10%
- Hearing, Cochlea, Tinnitus, Genetics
- Speech and Hearing top 5%
- Noise Effects and Management
Papers in
-
- SARS-CoV-2 and COVID-19 Research 3
- COVID-19 Clinical Research Studies 2
-
- Dialysis and Renal Disease Management 3
- Co-authors
- How‐Ran Guo (26 shared papers)Kow‐Tong Chen (8 shared papers)Kou-Huang Chen (3 shared papers)Hung‐Jung Lin (16 shared papers)Chien‐Cheng Huang (20 shared papers)Tsair‐Wei Chien (8 shared papers)Chih‐Wei Lu (5 shared papers)Cheng-Yao Lin (5 shared papers)
In The Last Decade
Shih‐Bin Su
61 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 151
- Sensory Systems 55
- Speech and Hearing 64
- Medical Laboratory Technology 11
- Infectious Diseases 104
- Epidemiology 175
Countries citing papers authored by Shih‐Bin Su
This map shows the geographic impact of Shih‐Bin Su'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 Shih‐Bin Su with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shih‐Bin Su more than expected).
Fields of papers citing papers by Shih‐Bin Su
This network shows the impact of papers produced by Shih‐Bin Su. 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 Shih‐Bin Su. The network helps show where Shih‐Bin Su may publish in the future.
Co-authors
The 25 scholars most cited alongside Shih‐Bin Su, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 62 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 144 | |
| 2 | 2016 | 91 | |
| 3 | 2022 | 78 | |
| 4 | 2005 | 74 | |
| 5 | 2008 | 48 | |
| 6 | 2021 | 39 | |
| 7 | 2008 | 39 | |
| 8 | 2005 | 35 | |
| 9 | 2006 | 32 | |
| 10 | 2012 | 31 | |
| 11 | 2011 | 31 | |
| 12 | 2017 | 24 | |
| 13 | 2019 | 24 | |
| 14 | 2014 | 23 | |
| 15 | 2011 | 20 | |
| 16 | 2002 | 20 | |
| 17 | 2015 | 20 | |
| 18 | 2008 | 20 | |
| 19 | 2016 | 18 | |
| 20 | 2015 | 17 |
About Shih‐Bin Su
Shih‐Bin Su is a scholar working on Infectious Diseases, Nephrology, Epidemiology, Experimental and Cognitive Psychology and Modeling and Simulation, having authored 62 papers that have together received 1.1k indexed citations. Recurring topics across this work include Workplace Health and Well-being (5 papers), COVID-19 epidemiological studies (3 papers), Sleep and Work-Related Fatigue (3 papers), Pesticide Exposure and Toxicity (3 papers), Dialysis and Renal Disease Management (3 papers), SARS-CoV-2 and COVID-19 Research (3 papers), Occupational Health and Safety Research (2 papers) and COVID-19 Clinical Research Studies (2 papers). The work is most often cited by research in Sensory Systems (55 citations), Speech and Hearing (64 citations), Medical Laboratory Technology (11 citations), Infectious Diseases (104 citations) and Epidemiology (175 citations). Shih‐Bin Su has collaborated with scholars based in Taiwan, China and Hong Kong. Frequent co-authors include How‐Ran Guo, Kow‐Tong Chen, Kou-Huang Chen, Hung‐Jung Lin, Chien‐Cheng Huang, Tsair‐Wei Chien, Chih‐Wei Lu, Cheng-Yao Lin, Jhi‐Joung Wang and Hsien‐Yi Wang. Their work appears in journals such as Medicine, Epidemiology, PLoS ONE, American Journal of Tropical Medicine and Hygiene and Renal Failure.
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.