Mao‐Yuan Su

2.0k 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 Cardiovascular Function and Risk Factors (18 papers), Advanced MRI Techniques and Applications (18 papers) and Cardiac Imaging and Diagnostics (17 papers). Mao‐Yuan Su is often cited by papers focused on Cardiovascular Function and Risk Factors (18 papers), Advanced MRI Techniques and Applications (18 papers) and Cardiac Imaging and Diagnostics (17 papers). Mao‐Yuan Su collaborates with scholars based in Taiwan, Germany and United States. 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, Timothy G. Reese, Ming-Ting Wu, Kuan-Rau Chiou and Van J. Wedeen 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

Peers

Mao‐Yuan Su
Tjeerd Germans Netherlands
Anish Bhuva United Kingdom
Jonathan D Suever United States
L. Iles Australia
Ricardo Wage United Kingdom
Mao‐Yuan Su
Citations per year, relative to Mao‐Yuan Su Mao‐Yuan Su (= 1×) peers Nicola Galea

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

20 of 20 papers shown
1.
2.
Huang, Kuan‐Chih, Ting‐Tse Lin, Jen‐Kuang Lee, et al.. (2024). Epicardial Adipose Tissue Is Associated With Geometry Alteration and Diastolic Dysfunction in Prediabetic Cardiomyopathy. The Journal of Clinical Endocrinology & Metabolism. 110(5). 1478–1487. 3 indexed citations
3.
Lin, Ting‐Tse, Chih‐Kuo Lee, Kuan‐Chih Huang, et al.. (2023). Differentiating the Prognostic Determinants of Myocardial Steatosis for Heart Failure With Preserved Ejection Fraction by Cardiac Magnetic Resonance Imaging. Journal of the American Heart Association. 12(17). e027781–e027781. 4 indexed citations
4.
Huang, Yu‐Sen, Zheng‐Wei Chen, Wen‐Jeng Lee, et al.. (2023). Treatment Response Evaluation by Computed Tomography Pulmonary Vasculature Analysis in Patients With Chronic Thromboembolic Pulmonary Hypertension. Korean Journal of Radiology. 24(4). 349–349. 4 indexed citations
5.
Huang, Yu‐Sen, Mao‐Yuan Su, Thomas Benkert, et al.. (2021). Applying Compressed Sensing Volumetric Interpolated Breath-Hold Examination and Spiral Ultrashort Echo Time Sequences for Lung Nodule Detection in MRI. Diagnostics. 12(1). 93–93. 12 indexed citations
6.
Su, Mao‐Yuan, Yu‐Sen Huang, Kelvin Chow, et al.. (2020). Is a timely assessment of the hematocrit necessary for cardiovascular magnetic resonance–derived extracellular volume measurements?. Journal of Cardiovascular Magnetic Resonance. 22(1). 77–77. 16 indexed citations
7.
Huang, Kuan‐Chih, et al.. (2020). Artificial Intelligence Aids Cardiac Image Quality Assessment for Improving Precision in Strain Measurements. JACC. Cardiovascular imaging. 14(2). 335–345. 27 indexed citations
8.
Su, Mao‐Yuan, Tien‐Min Lin, Jyh‐Ming Jimmy Juang, et al.. (2020). CMR-derived ECVs vary with myocardial region and associate with the regional wall thickness. Scientific Reports. 10(1). 20965–20965.
9.
Wang, Chih‐Yuan, et al.. (2019). Effect of Empagliflozin on Cardiac Function, Adiposity, and Diffuse Fibrosis in Patients with Type 2 Diabetes Mellitus. Scientific Reports. 9(1). 15348–15348. 33 indexed citations
10.
Wu, Cho‐Kai, Mao‐Yuan Su, Juey‐Jen Hwang, et al.. (2017). Evolutional change in epicardial fat and its correlation with myocardial diffuse fibrosis in heart failure patients. Journal of clinical lipidology. 11(6). 1421–1431. 77 indexed citations
11.
Chang, Chin‐Chen, et al.. (2016). Clinical feasibility of Gd-EOB-DTPA-enhanced MR imaging for assessing liver function: validation with ICG tests and parenchymal cell volume. Clinical Imaging. 40(4). 797–800. 6 indexed citations
12.
Lin, Lian‐Yu, Mao‐Yuan Su, Van-Truong Pham, et al.. (2016). Endocardial Remodeling in Heart Failure Patients with Impaired and Preserved Left Ventricular Systolic Function-A Magnetic Resonance Image Study. Scientific Reports. 6(1). 20868–20868. 6 indexed citations
13.
Kao, Hsien‐Li, Mao‐Shin Lin, Wen‐Chau Wu, et al.. (2015). Improvement of Cerebral Glucose Metabolism in Symptomatic Patients With Carotid Artery Stenosis After Stenting. Clinical Nuclear Medicine. 40(9). 701–707. 8 indexed citations
14.
Su, Mao‐Yuan, Lian‐Yu Lin, Yao‐Hui Tseng, et al.. (2014). CMR-Verified Diffuse Myocardial Fibrosis Is Associated With Diastolic Dysfunction in HFpEF. JACC. Cardiovascular imaging. 7(10). 991–997. 174 indexed citations
15.
Wu, Cho‐Kai, Yi‐Chih Wang, Jen‐Kuang Lee, et al.. (2013). Connective Tissue Growth Factor and Cardiac Diastolic Dysfunction: Human Data from the Taiwan Diastolic Heart Failure Registry and Molecular Basis by Cellular and Animal Models. European Journal of Heart Failure. 16(2). 163–172. 27 indexed citations
16.
Lin, Lian‐Yu, Mao‐Yuan Su, Jien‐Jiun Chen, et al.. (2013). Conductive Channels Identified With Contrast-Enhanced MR Imaging Predict Ventricular Tachycardia in Systolic Heart Failure. JACC. Cardiovascular imaging. 6(11). 1152–1159. 12 indexed citations
17.
Chen, Chun‐An, Wen‐Yih Isaac Tseng, Jou‐Kou Wang, et al.. (2012). Circulating biomarkers of collagen type I metabolism mark the right ventricular fibrosis and adverse markers of clinical outcome in adults with repaired tetralogy of Fallot. International Journal of Cardiology. 167(6). 2963–2968. 26 indexed citations
18.
Su, Mao‐Yuan, et al.. (2011). Exercise training increases myocardial perfusion in residual viable myocardium within infarct zone. Journal of Magnetic Resonance Imaging. 34(1). 60–68. 6 indexed citations
19.
Su, Mao‐Yuan, Kai‐Chien Yang, Chau‐Chung Wu, et al.. (2007). First-Pass Myocardial Perfusion Cardiovascular Magnetic Resonance at 3 Tesla. Journal of Cardiovascular Magnetic Resonance. 9(4). 633–644. 21 indexed citations
20.
Yu, Hsi‐Yu, Mao‐Yuan Su, Yih‐Sharng Chen, Fang‐Yue Lin, & Wen‐Yih Isaac Tseng. (2005). Mitral tetrahedron as a geometrical surrogate for chronic ischemic mitral regurgitation. American Journal of Physiology-Heart and Circulatory Physiology. 289(3). H1218–H1225. 9 indexed citations

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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