Chu-Pin Chu

1.6k total citations
13 papers, 1.3k citations indexed

About

Chu-Pin Chu is a scholar working on Endocrinology, Diabetes and Metabolism, Nephrology and Surgery. According to data from OpenAlex, Chu-Pin Chu has authored 13 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Endocrinology, Diabetes and Metabolism, 4 papers in Nephrology and 2 papers in Surgery. Recurrent topics in Chu-Pin Chu's work include Diabetes, Cardiovascular Risks, and Lipoproteins (4 papers), Diabetes Treatment and Management (3 papers) and Renal Diseases and Glomerulopathies (3 papers). Chu-Pin Chu is often cited by papers focused on Diabetes, Cardiovascular Risks, and Lipoproteins (4 papers), Diabetes Treatment and Management (3 papers) and Renal Diseases and Glomerulopathies (3 papers). Chu-Pin Chu collaborates with scholars based in United States and Switzerland. Chu-Pin Chu's co-authors include Pasquale Palumbo, L. Joseph Melton, David Ballard, Leonard T. Kurland, Daniel C. Connolly, Lila R. Elveback, Duane M. Ilstrup, Linda L. Humphrey, W. Michael O’Fallon and L. Joseph Melton and has published in prestigious journals such as Annals of Internal Medicine, Diabetes Care and Diabetes.

In The Last Decade

Chu-Pin Chu

13 papers receiving 1.2k citations

Peers

Chu-Pin Chu
Comparison fields: 5 of 88
  • Endocrinology, Diabetes and Metabolism 456
  • Nephrology 333
  • Cardiology and Cardiovascular Medicine 192
  • Surgery 188
  • Epidemiology 141
Replace Arif Hacıhasanoğlu with:
Arif Hacıhasanoğlu Türkiye
Jacob E. Poulsen Denmark
Halil Önder Ersöz Türkiye
Gary T.C. Ko Hong Kong
Jan Feyzi United States
Yun Kyung Jeon South Korea
Claudia Specchia Italy
R. T. Gansevoort Netherlands
Mehmet Yazıcı Türkiye
Anna Sanmartı́ Spain
Arif Hacıhasanoğlu Türkiye View profile →
Citations per field, relative to Chu-Pin Chu
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Citations per year, relative to Chu-Pin Chu
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Countries citing papers authored by Chu-Pin Chu

Since Specialization
Citations

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

Fields of papers citing papers by Chu-Pin Chu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chu-Pin Chu. 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 Chu-Pin Chu. The network helps show where Chu-Pin Chu may publish in the future.

Co-authorship network of co-authors of Chu-Pin Chu

This figure shows the co-authorship network connecting the top 25 collaborators of Chu-Pin Chu. A scholar is included among the top collaborators of Chu-Pin Chu 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 Chu-Pin Chu. Chu-Pin Chu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

13 of 13 papers shown
# Work Indexed citations
1 74
2 76
3 21
4 122
5 28
6 166
7 185
8 93
9 50
10 109
11 127
12 16
13 183

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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2026