Bin Que

665 citations
42 papers · 448 · h-index 11

Impact in

Papers in

Bin Que

37 papers receiving 443 citations

Peers

Bin Que
Comparison fields: 5 of 68
  • Immunology 104
  • Cardiology and Cardiovascular Medicine 88
  • Physiology 82
  • Genetics 22
  • Endocrine and Autonomic Systems 13
Replace Petros Moustardas with:
Petros Moustardas Sweden
Mariantonia Braile Italy
Anke C. Fender Germany
Benling Qi China
Jason A. Collett United States
Stéphanie Magnenat France
Maria T. K. Zaldivia Australia
Elisa Borgogni Italy
Ju Hee Lee Canada
Kenji Ashida Japan
Bin Que relative to Petros Moustardas Sweden Petros Moustardas's profile →
Citations per field
00.5×1.5×2.2×
Petros Moustardas · 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 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201863
2 201754
3 202252
4 201850
5 201944
6 201929
7 201529
8 201014
9 202314
10 201610
11 201510
12 202010
13 20238
14 20226
15 20145
16 20235
17 20245
18 20194
19 20234
20 20243

About Bin Que

Bin Que is a scholar working on Physiology, Cardiology and Cardiovascular Medicine, Surgery, Pulmonary and Respiratory Medicine and Internal Medicine, having authored 42 papers that have together received 448 indexed citations. Recurring topics across this work include Obstructive Sleep Apnea Research (14 papers), Coronary Interventions and Diagnostics (3 papers), Acute Myocardial Infarction Research (3 papers), Venous Thromboembolism Diagnosis and Management (2 papers), Cardiac, Anesthesia and Surgical Outcomes (2 papers), Chemotherapy-induced cardiotoxicity and mitigation (2 papers), Adipokines, Inflammation, and Metabolic Diseases (2 papers) and Atherosclerosis and Cardiovascular Diseases (2 papers). The work is most often cited by research in Immunology (104 citations), Cardiology and Cardiovascular Medicine (88 citations), Physiology (82 citations), Genetics (22 citations) and Endocrine and Autonomic Systems (13 citations). Bin Que has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Yingzhong Lin, Qingwei Ji, Hui Ai, Chao Chang, Jingyao Fan, Haiying Hu, Ying Shi, Wei Gong, Tao Zeng and Lei Shi. Their work appears in journals such as American Heart Journal, Journal of the American College of Cardiology, EBioMedicine, BMC Cardiovascular Disorders and Disease Markers.

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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