Hua-Fen Chen

529 total citations
15 papers, 385 citations indexed

About

Hua-Fen Chen is a scholar working on Surgery, Molecular Biology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Hua-Fen Chen has authored 15 papers receiving a total of 385 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Surgery, 5 papers in Molecular Biology and 5 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Hua-Fen Chen's work include Metabolism, Diabetes, and Cancer (4 papers), Stroke Rehabilitation and Recovery (2 papers) and Chronic Disease Management Strategies (2 papers). Hua-Fen Chen is often cited by papers focused on Metabolism, Diabetes, and Cancer (4 papers), Stroke Rehabilitation and Recovery (2 papers) and Chronic Disease Management Strategies (2 papers). Hua-Fen Chen collaborates with scholars based in Taiwan, United States and China. Hua-Fen Chen's co-authors include Chung‐Yi Li, Ming-Chung Ko, Pei‐Chun Chen, Ya‐Hui Chang, Chin‐Li Lu, Hsinyu Lee, Peter Chen, Wei‐Hung Lin, Li‐Jung Elizabeth Ku and Santi Martini and has published in prestigious journals such as PLoS ONE, Diabetes Care and Environment International.

In The Last Decade

Hua-Fen Chen

15 papers receiving 371 citations

Peers

Hua-Fen Chen
Comparison fields: 5 of 69
  • Endocrinology, Diabetes and Metabolism 151
  • Epidemiology 94
  • Surgery 83
  • Oncology 64
  • Cardiology and Cardiovascular Medicine 61
Replace Ahmet Kaya with:
Ahmet Kaya Türkiye
Alexander Shinkov Bulgaria
Antonis Polymeris Greece
Jan S.A.G. Schouten Netherlands
Carola Deischinger Austria
Paraskevi Pliatsika Greece
Karen Oppermann Brazil
Tae Yong Lee South Korea
Margaret Rees United Kingdom
Micah L. Olson United States
Ahmet Kaya Türkiye View profile →
Citations per field, relative to Hua-Fen Chen
Hua-Fen Chen · 1×
Citations per year, relative to Hua-Fen Chen
Hua-Fen Chen · 1×

Countries citing papers authored by Hua-Fen Chen

Since Specialization
Citations

This map shows the geographic impact of Hua-Fen Chen'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 Hua-Fen Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hua-Fen Chen more than expected).

Fields of papers citing papers by Hua-Fen Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hua-Fen Chen. 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 Hua-Fen Chen. The network helps show where Hua-Fen Chen may publish in the future.

Co-authorship network of co-authors of Hua-Fen Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Hua-Fen Chen. A scholar is included among the top collaborators of Hua-Fen Chen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hua-Fen Chen. Hua-Fen Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

15 of 15 papers shown
# Work Indexed citations
1 2
2 2
3 11
4 13
5 10
6 30
7 12
8 20
9 7
10 28
11 8
12 113
13 46
14 65
15 18

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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