Yangang Su

690 total citations
56 papers, 322 citations indexed

About

Yangang Su is a scholar working on Cardiology and Cardiovascular Medicine, Neurology and Complementary and alternative medicine. According to data from OpenAlex, Yangang Su has authored 56 papers receiving a total of 322 indexed citations (citations by other indexed papers that have themselves been cited), including 53 papers in Cardiology and Cardiovascular Medicine, 5 papers in Neurology and 4 papers in Complementary and alternative medicine. Recurrent topics in Yangang Su's work include Cardiac pacing and defibrillation studies (47 papers), Cardiac Arrhythmias and Treatments (31 papers) and Cardiac electrophysiology and arrhythmias (20 papers). Yangang Su is often cited by papers focused on Cardiac pacing and defibrillation studies (47 papers), Cardiac Arrhythmias and Treatments (31 papers) and Cardiac electrophysiology and arrhythmias (20 papers). Yangang Su collaborates with scholars based in China, United States and Sweden. Yangang Su's co-authors include Junbo Ge, Yixiu Liang, Xianhong Shu, Wenzhi Pan, Jingfeng Wang, Haiyan Chen, Wei Hua, Shalaimaiti Shali, Shengmei Qin and Shu Zhang and has published in prestigious journals such as Circulation, The Journal of Clinical Endocrinology & Metabolism and European Heart Journal.

In The Last Decade

Yangang Su

49 papers receiving 313 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yangang Su China 11 262 39 34 30 19 56 322
Rongfang Lan China 9 271 1.0× 38 1.0× 43 1.3× 43 1.4× 5 0.3× 18 340
Pedro Fernández United States 9 206 0.8× 35 0.9× 50 1.5× 11 0.4× 24 1.3× 19 319
Lihui Zheng China 9 150 0.6× 46 1.2× 69 2.0× 9 0.3× 27 1.4× 43 262
Virginia B. Hebl United States 11 451 1.7× 66 1.7× 116 3.4× 9 0.3× 21 1.1× 16 561
Richard Daly United Kingdom 7 172 0.7× 43 1.1× 14 0.4× 9 0.3× 19 1.0× 13 305
Mariemma Paccanaro Italy 7 325 1.2× 54 1.4× 53 1.6× 5 0.2× 60 3.2× 14 387
Simon Braumann Germany 9 64 0.2× 43 1.1× 39 1.1× 7 0.2× 10 0.5× 25 166
K Imataka Japan 7 149 0.6× 63 1.6× 46 1.4× 6 0.2× 25 1.3× 19 253
Richard Rodeheffer United States 4 326 1.2× 81 2.1× 107 3.1× 5 0.2× 35 1.8× 8 409

Countries citing papers authored by Yangang Su

Since Specialization
Citations

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

Fields of papers citing papers by Yangang Su

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yangang Su

This figure shows the co-authorship network connecting the top 25 collaborators of Yangang Su. A scholar is included among the top collaborators of Yangang 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 Yangang Su. Yangang 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.
Xue, Rui, et al.. (2025). C/EBPβ–VCAM1 axis in Kupffer cells promotes hepatic inflammation in MASLD. JHEP Reports. 7(8). 101418–101418. 2 indexed citations
2.
Huang, Zhenzhen, et al.. (2025). Kirenol attenuates pressure overload-induced heart failure by enhancing autophagy in macrophages. International Journal of Cardiology. 440. 133681–133681.
3.
Liang, Yixiu, Arunashis Sau, Joseph Barker, et al.. (2025). Artificial intelligence-enhanced electrocardiography to predict regurgitant valvular heart diseases: an international study. European Heart Journal. 46(44). 4823–4837. 2 indexed citations
4.
Ye, Yang, Xueying Chen, Shengjie Wu, et al.. (2023). Left Bundle Branch Pacing for Heart Failure and Left Bundle Branch Block Patients With Mildly Reduced and Preserved Left Ventricular Ejection Fraction. Canadian Journal of Cardiology. 39(11). 1598–1607. 1 indexed citations
5.
6.
Zhao, Shuang, Xiaoyao Li, Keping Chen, et al.. (2022). Interaction between electrical storm and left ventricular ejection fraction as predictors of mortality in patients with implantable cardioverter defibrillator: A Chinese cohort study. Frontiers in Cardiovascular Medicine. 9. 937655–937655. 1 indexed citations
7.
Liang, Yixiu, Ruifeng Ding, Jingfeng Wang, et al.. (2021). Prediction of response after cardiac resynchronization therapy with machine learning. International Journal of Cardiology. 344. 120–126. 13 indexed citations
8.
Li, Xiaoyao, Shuang Zhao, Keping Chen, et al.. (2020). Sex Differences in Physical Activity and Its Association With Cardiac Death and All-Cause Mortality in Patients With Implantable Cardioverter-Defibrillators. Frontiers in Cardiovascular Medicine. 7. 588622–588622. 2 indexed citations
9.
Huang, Dejia, Wei Hua, Quan Fang, et al.. (2020). Biventricular Pacemaker and Defibrillator Implantation in Patients with Chronic Heart Failure in China. ESC Heart Failure. 8(1). 546–554. 7 indexed citations
10.
Gong, Xue, Zhonghan Sun, Zheyong Huang, et al.. (2020). Circulating metabolite profiles to predict response to cardiac resynchronization therapy. BMC Cardiovascular Disorders. 20(1). 178–178. 3 indexed citations
11.
Chen, Xueying, Jingfeng Wang, Shengmei Qin, et al.. (2019). The feasibility and efficacy of His-Purkinje system pacing in chronic heart failure with permanent atrial fibrillation. 23(5). 405–410.
12.
Zhang, Xinwei, Zhiyong Qian, Haipeng Tang, et al.. (2019). A new method to recommend left ventricular lead positions for improved CRT volumetric response and long-term prognosis. Journal of Nuclear Cardiology. 28(2). 672–684. 10 indexed citations
13.
Liu, Wenheng, Keping Chen, Yangang Su, et al.. (2016). Patient acceptance of and satisfaction with the Carelink remote monitoring system. 20(6). 481–485.
14.
Su, Yangang, Shengmei Qin, Jian Xu, et al.. (2016). [Efficacy of biventricular pacing on preventing heart failure in patients with high degree atrioventricular block (BIVPACE-AVB Trial)].. PubMed. 44(4). 331–7. 3 indexed citations
15.
16.
Shali, Shalaimaiti, Yangang Su, & Junbo Ge. (2016). Interatrial septal pacing to suppress atrial fibrillation in patients with dual chamber pacemakers: A meta-analysis of randomized, controlled trials. International Journal of Cardiology. 219. 421–427. 14 indexed citations
17.
Zhao, Shuang, Keping Chen, Yangang Su, et al.. (2015). The role of variability in night-time mean heart rate on the prediction of ventricular arrhythmias and all-cause mortality in implantable cardioverter defibrillator patients. EP Europace. 17(suppl 2). ii76–ii82. 6 indexed citations
18.
Kang, Yu, Leilei Cheng, Jie Cui, et al.. (2015). A new score system for predicting response to cardiac resynchronization therapy. Cardiology Journal. 22(2). 179–187. 10 indexed citations
19.
Qin, Shengmei, Hongcheng Shi, Yangang Su, et al.. (2015). Can the Prognosis of Cardiac Resynchronization Therapy Be Predicted by Gated SPECT?. Clinical Nuclear Medicine. 40(10). 786–792. 1 indexed citations
20.
Liang, Yixiu, Wenzhi Pan, Yangang Su, & Junbo Ge. (2011). Meta-Analysis of Randomized Controlled Trials Comparing Isolated Left Ventricular and Biventricular Pacing in Patients With Chronic Heart Failure. The American Journal of Cardiology. 108(8). 1160–1165. 23 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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