Yi‐Chang Cheng

1.9k total citations · 1 hit paper
18 papers, 1.4k citations indexed

About

Yi‐Chang Cheng is a scholar working on Cardiology and Cardiovascular Medicine, Molecular Biology and Infectious Diseases. According to data from OpenAlex, Yi‐Chang Cheng has authored 18 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Cardiology and Cardiovascular Medicine, 5 papers in Molecular Biology and 4 papers in Infectious Diseases. Recurrent topics in Yi‐Chang Cheng's work include Cardiac Fibrosis and Remodeling (6 papers), Signaling Pathways in Disease (3 papers) and SARS-CoV-2 and COVID-19 Research (2 papers). Yi‐Chang Cheng is often cited by papers focused on Cardiac Fibrosis and Remodeling (6 papers), Signaling Pathways in Disease (3 papers) and SARS-CoV-2 and COVID-19 Research (2 papers). Yi‐Chang Cheng collaborates with scholars based in Taiwan, China and Japan. Yi‐Chang Cheng's co-authors include Paul K.S. Chan, Y.O.Y. Soo, Gregory Cheng, Raymond Wong, Margaret H.L. Ng, Wing S. Wong, Kwok Chuen Wong, Chi Bon Leung, Chih‐Yang Huang and David S.C. Hui and has published in prestigious journals such as Food Chemistry, Emerging infectious diseases and Journal of Ethnopharmacology.

In The Last Decade

Yi‐Chang Cheng

18 papers receiving 1.3k citations

Hit Papers

Use of convalescent plasma therapy in SARS patients in Ho... 2004 2026 2011 2018 2004 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yi‐Chang Cheng Taiwan 12 898 276 208 163 96 18 1.4k
Kaiming Wang Canada 7 1.1k 1.3× 553 2.0× 271 1.3× 147 0.9× 106 1.1× 20 1.7k
Weina Guo China 15 910 1.0× 430 1.6× 275 1.3× 64 0.4× 272 2.8× 29 1.6k
Peiwen Zhou China 6 983 1.1× 366 1.3× 221 1.1× 67 0.4× 89 0.9× 11 1.4k
Tielong Chen China 13 613 0.7× 339 1.2× 149 0.7× 41 0.3× 140 1.5× 43 1.1k
Manman Geng China 12 885 1.0× 300 1.1× 330 1.6× 62 0.4× 85 0.9× 19 1.5k
Yongjiu Xiao China 8 594 0.7× 244 0.9× 197 0.9× 46 0.3× 151 1.6× 15 1.1k
Xiuwen Yang China 6 570 0.6× 261 0.9× 161 0.8× 46 0.3× 72 0.8× 17 914
Ramy Salem Egypt 4 736 0.8× 399 1.4× 221 1.1× 68 0.4× 123 1.3× 7 1.2k
Shaoying Huang China 9 741 0.8× 416 1.5× 232 1.1× 62 0.4× 102 1.1× 13 1.5k

Countries citing papers authored by Yi‐Chang Cheng

Since Specialization
Citations

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

Fields of papers citing papers by Yi‐Chang Cheng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yi‐Chang Cheng. 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 Yi‐Chang Cheng. The network helps show where Yi‐Chang Cheng may publish in the future.

Co-authorship network of co-authors of Yi‐Chang Cheng

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

All Works

18 of 18 papers shown
1.
Luo, Xin, Yi‐Chang Cheng, Chen Wu, & Jia He. (2023). [An interpretable machine learning-based prediction model for risk of death for patients with ischemic stroke in intensive care unit].. PubMed. 43(7). 1241–1247. 1 indexed citations
2.
Lin, Yu‐Chen, Wei‐Wen Kuo, Chia-Yao Shen, et al.. (2018). Platycodin D Reverses Pathological Cardiac Hypertrophy and Fibrosis in Spontaneously Hypertensive Rats. The American Journal of Chinese Medicine. 46(3). 537–549. 34 indexed citations
3.
Cheng, Yi‐Chang, Mu-Hsin Chang, Cheng‐Chih Tsai, et al.. (2012). Garlic oil attenuates the cardiac apoptosis in hamster-fed with hypercholesterol diet. Food Chemistry. 136(3-4). 1296–1302. 11 indexed citations
4.
Lai, Chao‐Hung, Mu-Hsin Chang, Gwo‐Ping Jong, et al.. (2011). IGF-II and MMP9 as surgical repair indicators of ventricular septal defects. Clinica Chimica Acta. 412(9-10). 761–765. 2 indexed citations
5.
Lai, Tung‐Yuan, Yueh-Sheng Chen, Fuu‐Jen Tsai, et al.. (2010). Dilong: Role in Peripheral Nerve Regeneration. Evidence-based Complementary and Alternative Medicine. 2011(1). 380809–380809. 17 indexed citations
6.
Lai, Chao‐Hung, Chia‐Hua Kuo, Wen‐Yuan Lin, et al.. (2010). Carthamus tinctorius L. prevents LPS-induced TNFα signaling activation and cell apoptosis through JNK1/2–NFκB pathway inhibition in H9c2 cardiomyoblast cells. Journal of Ethnopharmacology. 130(3). 505–513. 71 indexed citations
7.
Cheng, Yi‐Chang, Wei‐Wen Kuo, James A. Lin, et al.. (2010). Ameliorate Effects of Li‐Fu Formula on IL‐6‐Mediated Cardiac Hypertrophy in Hamsters Fed with a Hyper‐Cholesterol Diet. Evidence-based Complementary and Alternative Medicine. 2011(1). 485471–485471. 2 indexed citations
8.
Cheng, Yi‐Chang, Wei‐Wen Kuo, Hsi‐Chin Wu, et al.. (2009). ZAK induces MMP-2 activity via JNK/p38 signals and reduces MMP-9 activity by increasing TIMP-1/2 expression in H9c2 cardiomyoblast cells. Molecular and Cellular Biochemistry. 325(1-2). 69–77. 19 indexed citations
9.
Lin, Wei‐Ching, Yung‐Fang Chen, Chien‐Heng Lin, et al.. (2009). Reappraisal of the Management and Outcome of Emphysematous Pyelonephritis. The Kaohsiung Journal of Medical Sciences. 25(1). 16–24. 5 indexed citations
10.
Cheng, Yi‐Chang, Li-Mien Chen, Mu-Hsin Chang, et al.. (2009). Lipopolysaccharide upregulates uPA, MMP-2 and MMP-9 via ERK1/2 signaling in H9c2 cardiomyoblast cells. Molecular and Cellular Biochemistry. 325(1-2). 15–23. 39 indexed citations
11.
Chen, Yueh-Sheng, Fuu‐Jen Tsai, Wei‐Wen Kuo, et al.. (2009). Proliferative Effects of Chishao on Schwann Cells are FGF-uPA, and ERK- and JNK-Dependent. The American Journal of Chinese Medicine. 37(6). 1191–1202. 5 indexed citations
12.
13.
Liu, Chung‐Jung, Yi‐Chang Cheng, Hsi-Hsien Hsu, et al.. (2008). Lipopolysaccharide induces cellular hypertrophy through calcineurin/NFAT-3 signaling pathway in H9c2 myocardiac cells. Molecular and Cellular Biochemistry. 313(1-2). 167–178. 54 indexed citations
14.
Cheng, Yi‐Chang, Wei-Wen Kuo, Chieh‐Hsi Wu, et al.. (2008). Iron status and cardiovascular risk factors in patients with haemodialysis versus patients with ischaemic heart disease. Nephrology. 14(1). 65–69. 3 indexed citations
15.
Chen, Wei-Kung, et al.. (2005). The Impact of the SARS Outbreak on an Urban Emergency Department in Taiwan. Medical Care. 43(2). 168–172. 61 indexed citations
16.
Chen, Wei-Kung, et al.. (2005). Emergency Department Response to SARS, Taiwan. Emerging infectious diseases. 11(7). 1067–1073. 19 indexed citations
17.
Soo, Y.O.Y., Yi‐Chang Cheng, Raymond Wong, et al.. (2004). Retrospective comparison of convalescent plasma with continuing high-dose methylprednisolone treatment in SARS patients. Clinical Microbiology and Infection. 10(7). 676–678. 284 indexed citations
18.
Cheng, Yi‐Chang, Raymond Wong, Y.O.Y. Soo, et al.. (2004). Use of convalescent plasma therapy in SARS patients in Hong Kong. European Journal of Clinical Microbiology & Infectious Diseases. 24(1). 44–46. 674 indexed citations breakdown →

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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