Te‐Lin Hsia

25 total papers · 4.3k total citations
10 papers, 144 citations indexed

About

Te‐Lin Hsia is a scholar working on Endocrinology, Diabetes and Metabolism, Epidemiology and Surgery. According to data from OpenAlex, Te‐Lin Hsia has authored 10 papers receiving a total of 144 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Endocrinology, Diabetes and Metabolism, 4 papers in Epidemiology and 1 paper in Surgery. Recurrent topics in Te‐Lin Hsia's work include Diabetes, Cardiovascular Risks, and Lipoproteins (4 papers), Diabetes Management and Research (4 papers) and Liver Disease Diagnosis and Treatment (3 papers). Te‐Lin Hsia is often cited by papers focused on Diabetes, Cardiovascular Risks, and Lipoproteins (4 papers), Diabetes Management and Research (4 papers) and Liver Disease Diagnosis and Treatment (3 papers). Te‐Lin Hsia collaborates with scholars based in Taiwan. Te‐Lin Hsia's co-authors include Ching‐Chieh Su, Dee Pei, Chang‐Hsun Hsieh, Wen‐Ya Ma, Kuo‐Cheng Lu, Li‐Yu Tsai, Hung‐Yuan Li, Jung‐Nan Wei, Yen‐Lin Chen and Tao‐Hsin Tung and has published in prestigious journals such as Life Sciences, Medicine and Clinica Chimica Acta.

In The Last Decade

Te‐Lin Hsia

10 papers receiving 141 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Te‐Lin Hsia 87 50 24 23 14 10 144
Elisa Manicardi 80 0.9× 65 1.3× 70 2.9× 38 1.7× 14 1.0× 10 270
Maliheh Khoramdad 41 0.5× 36 0.7× 30 1.3× 42 1.8× 18 1.3× 10 217
Guadalupe Ruiz‐Vivanco 45 0.5× 41 0.8× 15 0.6× 27 1.2× 28 2.0× 14 137
Kazuhide Ishikura 87 1.0× 93 1.9× 21 0.9× 25 1.1× 41 2.9× 12 202
Qinglin Lou 82 0.9× 64 1.3× 25 1.0× 14 0.6× 24 1.7× 14 222
Daniel Panarotto 82 0.9× 73 1.5× 38 1.6× 65 2.8× 25 1.8× 11 205
Nicole Aumann 114 1.3× 76 1.5× 32 1.3× 26 1.1× 41 2.9× 8 235
Zewei Shen 38 0.4× 49 1.0× 29 1.2× 54 2.3× 26 1.9× 7 215
Christoph Schnack 72 0.8× 32 0.6× 28 1.2× 31 1.3× 28 2.0× 9 198
Yuan Liu 128 1.5× 82 1.6× 35 1.5× 21 0.9× 39 2.8× 11 222

Countries citing papers authored by Te‐Lin Hsia

Since Specialization
Citations

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

Fields of papers citing papers by Te‐Lin Hsia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Te‐Lin Hsia

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

All Works

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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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