Mao‐Yuan Su

66 total papers · 1.9k total citations
57 papers, 1.4k citations indexed

About

Mao‐Yuan Su is a scholar working on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Mao‐Yuan Su has authored 57 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Cardiology and Cardiovascular Medicine, 24 papers in Radiology, Nuclear Medicine and Imaging and 12 papers in Molecular Biology. Recurrent topics in Mao‐Yuan Su's work include Advanced MRI Techniques and Applications (18 papers), Cardiovascular Function and Risk Factors (18 papers) and Cardiac Imaging and Diagnostics (17 papers). Mao‐Yuan Su is often cited by papers focused on Advanced MRI Techniques and Applications (18 papers), Cardiovascular Function and Risk Factors (18 papers) and Cardiac Imaging and Diagnostics (17 papers). Mao‐Yuan Su collaborates with scholars based in Taiwan, United States and Germany. Mao‐Yuan Su's co-authors include Wen‐Yih Isaac Tseng, Cho‐Kai Wu, Lian‐Yu Lin, Jiunn-Lee Lin, Juey‐Jen Hwang, Chin‐Chen Chang, Van J. Wedeen, Kuan-Rau Chiou, Timothy G. Reese and Ming-Ting Wu and has published in prestigious journals such as Circulation, PLoS ONE and The Journal of Clinical Endocrinology & Metabolism.

In The Last Decade

Mao‐Yuan Su

51 papers receiving 1.4k citations

Author Peers

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

Author Last Decade Papers Cites
Mao‐Yuan Su 864 570 251 156 109 57 1.4k
Marjorie Gabel 1.1k 1.2× 424 0.7× 234 0.9× 171 1.1× 94 0.9× 52 1.4k
François Tournoux 1.0k 1.2× 488 0.9× 205 0.8× 168 1.1× 133 1.2× 65 1.4k
Fátima Franco 1.0k 1.2× 329 0.6× 199 0.8× 333 2.1× 122 1.1× 57 1.6k
David Broadbent 1.0k 1.2× 980 1.7× 183 0.7× 149 1.0× 144 1.3× 38 1.6k
Yasmin S. Hamirani 704 0.8× 481 0.8× 302 1.2× 61 0.4× 198 1.8× 73 1.1k
C Benvenuti 814 0.9× 508 0.9× 333 1.3× 107 0.7× 60 0.6× 57 1.3k
J. William O’Connell 907 1.0× 400 0.7× 143 0.6× 100 0.6× 58 0.5× 41 1.3k
José Cláudio Meneghetti 540 0.6× 478 0.8× 238 0.9× 74 0.5× 165 1.5× 58 1.2k
Peder Sörensson 864 1.0× 566 1.0× 283 1.1× 167 1.1× 198 1.8× 82 1.4k
Nicola Galea 837 1.0× 574 1.0× 262 1.0× 239 1.5× 281 2.6× 102 1.6k

Countries citing papers authored by Mao‐Yuan Su

Since Specialization
Citations

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

Fields of papers citing papers by Mao‐Yuan Su

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mao‐Yuan Su. 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 Mao‐Yuan Su. The network helps show where Mao‐Yuan Su may publish in the future.

Co-authorship network of co-authors of Mao‐Yuan Su

This figure shows the co-authorship network connecting the top 25 collaborators of Mao‐Yuan Su. A scholar is included among the top collaborators of Mao‐Yuan Su 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 Mao‐Yuan Su. Mao‐Yuan Su 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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