Chunmei Qi

765 total citations
21 papers, 281 citations indexed

About

Chunmei Qi is a scholar working on Cardiology and Cardiovascular Medicine, Surgery and Molecular Biology. According to data from OpenAlex, Chunmei Qi has authored 21 papers receiving a total of 281 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Cardiology and Cardiovascular Medicine, 6 papers in Surgery and 4 papers in Molecular Biology. Recurrent topics in Chunmei Qi's work include Cardiovascular Disease and Adiposity (4 papers), Cardiac Imaging and Diagnostics (4 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (3 papers). Chunmei Qi is often cited by papers focused on Cardiovascular Disease and Adiposity (4 papers), Cardiac Imaging and Diagnostics (4 papers) and Diabetes, Cardiovascular Risks, and Lipoproteins (3 papers). Chunmei Qi collaborates with scholars based in China, United Kingdom and United States. Chunmei Qi's co-authors include Lei Gong, Jingjing Jin, Sai Zhang, Li Li, Yu Zhang, Ning Gu, Yanni Jiang, Shaoqian Li, Jun Wang and Ming Ma and has published in prestigious journals such as PLoS ONE, Biomaterials and Scientific Reports.

In The Last Decade

Chunmei Qi

18 papers receiving 275 citations

Peers

Chunmei Qi

CCM

ONCOL

SURGE

EPIDE

Wenyu Guo China

He Bai China

Xiaoyu Zhou China

Edvardas Žurauskas Lithuania

Yibo Tang China

Min Jin Lee South Korea

Xiaolin Liu China

Erik M. Dunki-Jacobs United States

Gezim Bala Belgium

Eisuke Ueshima Japan

Wenyu Guo China

Chunmei Qi

64 ×0.6

CCM

49 ×0.7

ONCOL

95 ×2.0

66 ×1.5

SURGE

57 ×1.4

EPIDE

Citations per year, relative to Chunmei Qi Chunmei Qi (= 1×) peers Wenyu Guo

Countries citing papers authored by Chunmei Qi

Since Specialization

Citations

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

Fields of papers citing papers by Chunmei Qi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chunmei Qi

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

All Works

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20 of 20 papers shown

Hu, Yanan, et al.. (2025). Clinical prediction study on the risk of atrial fibrillation in hypertensive patients based on metabolism, inflammation, and gender differences. Scientific Reports. 15(1). 12678–12678. 1 indexed citations

Liu, Shuang, et al.. (2025). Analysis of Metabolic Risk Factors for Microcirculation Disorders Post-Percutaneous Coronary Intervention and Predictive Model Construction: A Study on Patients with Unstable Angina. Reviews in Cardiovascular Medicine. 26(1). 25739–25739. 1 indexed citations

Li, Kangming, Shizhong Chen, Yanan Hu, & Chunmei Qi. (2025). Exploring the role of the atherogenic index of plasma as a mediator between body roundness Index and cardiovascular events in older adults: a NHANES-based study. Frontiers in Cardiovascular Medicine. 12. 1506603–1506603.

Liu, Shuang, et al.. (2024). GSEA analysis identifies potential drug targets and their interaction networks in coronary microcirculation disorders. SLAS TECHNOLOGY. 29(4). 100152–100152. 2 indexed citations

Zhang, Huisheng, et al.. (2023). Performance bounds of complex-valued nonlinear estimators in learning systems. Neurocomputing. 557. 126681–126681. 2 indexed citations

Chen, Xuejin, et al.. (2023). Myocardial Perfusion in ST-Segment Elevation Myocardial Infarction Patients After Percutaneous Coronary Intervention: Influencing Factors and Intervention Strategies. Cureus. 15(8). e42841–e42841. 1 indexed citations

Wang, Lili, et al.. (2023). Correlation between dietary inflammation and mortality among hyperlipidemics. Lipids in Health and Disease. 22(1). 206–206. 5 indexed citations

Qi, Chunmei, et al.. (2022). Emergency Nursing of Patients with Acute Left Heart Failure. 6(1).

Qi, Chunmei, et al.. (2022). Batch gradient neuro-fuzzy learning method with smoothing L0 regularization for the first-order Takagi-Sugeno system. 11–15.

10.

Qi, Chunmei. (2019). The Relationship between Lipoprotein a and Glycosylated Hemoglobin and the Degree of Coronary Artery Stenosis in Non-Diabetic Coronary Heart Disease Patients. Biomedical Journal of Scientific & Technical Research. 21(4). 2 indexed citations

11.

Peng, Cheng, et al.. (2019). Study on Connective Tissue Growth Factor Expressed in Patients with ST-Segment Elevation Myocardial Infarction.. PubMed. 35(4). 355–359. 1 indexed citations

12.

Wang, Zhou, et al.. (2019). The Relationship Between Lipoprotein A and Glycosylated Hemoglobin and The Degree of Coronary Artery Stenosis in Non-Diabetic Coronary Heart Disease Patients. RePEc: Research Papers in Economics. 3(4). 2 indexed citations

13.

Zhang, Sai, et al.. (2018). Predictive value of neutrophil to lymphocyte ratio in patients with acute ST segment elevation myocardial infarction after percutaneous coronary intervention: a meta-analysis. BMC Cardiovascular Disorders. 18(1). 75–75. 123 indexed citations

14.

Hao, Ji, et al.. (2016). Clinical observation of effect of Ivabradine in the treatment of patients with chronic obstructive pulmonary disease complicated with angina pectoris. 21(6). 475–477. 1 indexed citations

15.

Qi, Chunmei, et al.. (2016). Experimental study of USPIO-enhanced MRI in the detection of atherosclerotic plaque and the intervention of atorvastatin. Experimental and Therapeutic Medicine. 12(1). 141–146. 7 indexed citations

16.

Qi, Chunmei, Lili Du, Dongye Li, et al.. (2015). Detection of Vulnerable Atherosclerotic Plaques in Experimental Atherosclerosis with the USPIO-Enhanced MRI. Cell Biochemistry and Biophysics. 73(2). 331–337. 7 indexed citations

17.

Qi, Chunmei, Dongye Li, Lei Gong, et al.. (2015). Identifying Vulnerable Atherosclerotic Plaque in Rabbits Using DMSA-USPIO Enhanced Magnetic Resonance Imaging to Investigate the Effect of Atorvastatin. PLoS ONE. 10(5). e0125677–e0125677. 12 indexed citations

18.

Wang, Yuehua, Ming Ma, Yu Zhang, et al.. (2012). CT/fluorescence dual-modal nanoemulsion platform for investigating atherosclerotic plaques. Biomaterials. 34(1). 209–216. 67 indexed citations

19.

Jiang, Yibo, Lijuan Chen, Yaoliang Tang, et al.. (2009). HO-1 gene overexpression enhances the beneficial effects of superparamagnetic iron oxide labeled bone marrow stromal cells transplantation in swine hearts underwent ischemia/reperfusion: an MRI study. Basic Research in Cardiology. 105(3). 431–442. 27 indexed citations

20.

Qi, Chunmei, Jun Wang, & Shaoqian Li. (2009). Weighted-Clustering Cooperative Spectrum Sensing in Cognitive Radio Context. 102–106. 18 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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