Wei‐Hung Lin

3.7k citations
160 papers · 2.7k indexed · h-index 29

Impact in

Papers in

Wei‐Hung Lin

147 papers receiving 2.6k citations

Peers

Wei‐Hung Lin
Comparison fields: 5 of 163
  • Endocrinology 279
  • Molecular Medicine 269
  • Computer Vision and Pattern Recognition 567
  • Microbiology 108
  • Media Technology 103
Replace Christoph Mayer with:
Christoph Mayer Germany
Susu M. Zughaier Qatar
Yun Shi China
Luís Pedro Coelho Germany
Takeshi Kobayashi Japan
Fen Hu China
Lihua Guo China
Giri Narasimhan United States
Bjarne Kjær Ersbøll Denmark
James E. Kirby United States
Wei‐Hung Lin relative to Christoph Mayer Germany Christoph Mayer's profile →
Citations per field
00.5×8.6×
Christoph Mayer · 1×
Citations per year

Countries citing papers authored by Wei‐Hung Lin

Since Specialization
Citations

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

Fields of papers citing papers by Wei‐Hung Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wei‐Hung Lin. 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 Wei‐Hung Lin. The network helps show where Wei‐Hung Lin may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20252
3 20241
4 20245
5 20243
6 20240
7 20240
8 20243
9 20239
10 20235
11 20232
12 20236
13 20233
14 20228
15 202127
16 20211
17 202023
18 201811
19 201517
20 201436

About Wei‐Hung Lin

Wei‐Hung Lin is a scholar working on Endocrinology, Molecular Medicine, Nephrology, Computer Vision and Pattern Recognition and Endocrinology, Diabetes and Metabolism, having authored 160 papers that have together received 2.7k indexed citations. Recurring topics across this work include Urinary Tract Infections Management (18 papers), Antibiotic Resistance in Bacteria (17 papers), Escherichia coli research studies (17 papers), Bacteriophages and microbial interactions (16 papers), Diabetes Treatment and Management (9 papers), Advanced Steganography and Watermarking Techniques (9 papers), Diabetes Management and Research (8 papers) and Dialysis and Renal Disease Management (8 papers). The work is most often cited by research in Endocrinology (279 citations), Molecular Medicine (269 citations), Computer Vision and Pattern Recognition (567 citations), Microbiology (108 citations) and Media Technology (103 citations). Wei‐Hung Lin has collaborated with scholars based in Taiwan, China and United States. Frequent co-authors include Shi‐Jinn Horng, Yuh-Rau Wang, Ming-Cheng Wang, Tzong‐Wann Kao, Chin‐Chung Tseng, Yi Pan, Jiunn-Jong Wu, Ching‐Hao Teng, Pingzhi Fan and Cheng‐Ling Lee. Their work appears in journals such as Journal of Microbiology Immunology and Infection, Frontiers in Microbiology, Expert Systems with Applications, European Journal of Clinical Microbiology & Infectious Diseases and Journal of Infection and Public Health.

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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