Shu‐Chun Kuo

427 citations
36 papers · 309 indexed · h-index 13

Shu‐Chun Kuo

33 papers receiving 305 citations

Peers

Shu‐Chun Kuo
Comparison fields: 5 of 103
  • Modeling and Simulation 45
  • Statistics, Probability and Uncertainty 66
  • Health Informatics 7
  • Ophthalmology 24
  • Developmental Neuroscience 9
Replace Mudit Agarwal with:
Mudit Agarwal India
Julian R. Homburger United States
Cheri K. Walker United States
Amit Mittal India
Lucy D’Agostino McGowan United States
Sophie Graham United Kingdom
Iffat Shams Canada
Zahra Emami Iran
Eun Soo Kim South Korea
Nicolás Ballarini Austria
Shu‐Chun Kuo relative to Mudit Agarwal India Mudit Agarwal's profile →
Citations per field
00.5×
Mudit Agarwal · 1×
Citations per year

Countries citing papers authored by Shu‐Chun Kuo

Since Specialization
Citations

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

Fields of papers citing papers by Shu‐Chun Kuo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shu‐Chun Kuo. 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 Shu‐Chun Kuo. The network helps show where Shu‐Chun Kuo may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20252
2 20241
3 20242
4 20243
5 20241
6 20230
7 20231
8 20231
9 20229
10 202221
11 202117
12 20212
13 20212
14 20217
15 202014
16 202012
17 201713
18 20176
19 201315
20 200613

About Shu‐Chun Kuo

Shu‐Chun Kuo is a scholar working on Ophthalmology, Statistics, Probability and Uncertainty, Modeling and Simulation, Family Practice and Organizational Behavior and Human Resource Management, having authored 36 papers that have together received 309 indexed citations. Recurring topics across this work include Retinal Diseases and Treatments (6 papers), scientometrics and bibliometrics research (5 papers), Meta-analysis and systematic reviews (5 papers), Glaucoma and retinal disorders (4 papers), Retinal and Optic Conditions (4 papers), Retinal Imaging and Analysis (3 papers), Data-Driven Disease Surveillance (3 papers) and COVID-19 epidemiological studies (3 papers). The work is most often cited by research in Modeling and Simulation (45 citations), Statistics, Probability and Uncertainty (66 citations), Health Informatics (7 citations), Ophthalmology (24 citations) and Developmental Neuroscience (9 citations). Shu‐Chun Kuo has collaborated with scholars based in Taiwan, United Kingdom and Japan. Frequent co-authors include Tsair‐Wei Chien, Yu-Tsen Yeh, Wei‐Chih Kan, Hsien‐Yi Wang, Willy Chou, Po‐Hsin Chou, Juei‐Tang Cheng, Ching‐Ping Chang, Hung‐Jung Lin and Yingxiao Li. Their work appears in journals such as Medicine, Scientometrics, JAMA Network Open, BMC Ophthalmology and Asian Journal of Andrology.

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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