Bin Que

707 citations
48 papers · 518 · h-index 10

Impact in

    • Cardiac Fibrosis and Remodeling
    • Blood Pressure and Hypertension Studies
    • Chemotherapy-induced cardiotoxicity and mitigation
    • Acute Myocardial Infarction Research
    • Renin-Angiotensin System Studies
    • Atherosclerosis and Cardiovascular Diseases

Papers in

Bin Que

41 papers receiving 511 citations

Peers

Bin Que
Comparison fields: 5 of 58
  • Cardiology and Cardiovascular Medicine 165
  • Immunology 106
  • Physiology 117
  • Genetics 29
  • Oncology 35
Replace Lucien Sambin with:
Lucien Sambin France
Elisabeth Bjørkelund Norway
Katsuya Chinen Japan
Takahiro Shirasawa Japan
Aytun Çanğa Türkiye
Amir Aziz United Kingdom
Denise Cristiana Faro Italy
Alexander A. Kremzer Ukraine
Mohamed Khayata United States
Yuriko Niitsuma Japan
Bin Que relative to Lucien Sambin France Lucien Sambin's profile →
Citations per field
00.5×2×3×3.7×
Lucien Sambin · 1×
Citations per year

Countries citing papers authored by Bin Que

Since Specialization
Citations

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

Fields of papers citing papers by Bin Que

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Bin Que, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Bin Que Line = papers co-authored together Bin Que links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201864
2 201761
3 202261
4 201851
5 201846
6 201533
7 201930
8 202318
9 202316
10 201611
11 201510
12 202010
13 20239
14 20088
15 20227
16 20237
17 20247
18 20236
19 20145
20 20195

About Bin Que

Bin Que is a scholar working on Physiology, Cardiology and Cardiovascular Medicine, Surgery, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine, having authored 48 papers that have together received 518 indexed citations. Recurring topics across this work include Obstructive Sleep Apnea Research (19 papers), Acute Myocardial Infarction Research (11 papers), Coronary Interventions and Diagnostics (6 papers), Cardiac Imaging and Diagnostics (4 papers), Aortic Disease and Treatment Approaches (4 papers), Atherosclerosis and Cardiovascular Diseases (3 papers), Lipoproteins and Cardiovascular Health (2 papers) and Antiplatelet Therapy and Cardiovascular Diseases (2 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (165 citations), Immunology (106 citations), Physiology (117 citations), Genetics (29 citations) and Oncology (35 citations). Bin Que has collaborated with scholars based in China, United States and Nigeria. Frequent co-authors include Hui Ai, Yingzhong Lin, Qingwei Ji, Yan Yan, Wei Gong, Jingyao Fan, Changsheng Ma, Shao-Ping Nie, Chao Chien Chang and Xiao Wang. Their work appears in journals such as Journal of the American College of Cardiology, American Heart Journal, Journal of the American Heart Association, BMC Pulmonary Medicine and European Heart Journal - Cardiovascular Imaging.

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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