Bin Que

643 citations
41 papers · 430 indexed · h-index 11

Impact in

Papers in

Bin Que

37 papers receiving 425 citations

Peers

Bin Que
Comparison fields: 5 of 77
  • Cardiology and Cardiovascular Medicine 141
  • Immunology 127
  • Endocrine and Autonomic Systems 31
  • Physiology 90
  • Pulmonary and Respiratory Medicine 77
Replace Satoshi Terao with:
Satoshi Terao Japan
Huili Lin China
Shathiyah Kulandavelu United States
Julie Labonté Canada
Young Kuk Cho South Korea
Hongyu Zhang China
Hakan Tıkız Türkiye
Tarik Hadi France
Yongchun Cui China
Bin Que relative to Satoshi Terao Japan Satoshi Terao's profile →
Citations per field
00.5×4.3×
Satoshi Terao · 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 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201864
2 201754
3 201847
4 202244
5 201942
6 201529
7 201929
8 201014
9 202313
10 201610
11 202010
12 20159
13 20237
14 20226
15 20235
16 20145
17 20244
18 20234
19 20194
20 20243

About Bin Que

Bin Que is a scholar working on Internal Medicine, Cardiology and Cardiovascular Medicine, Physiology, Pulmonary and Respiratory Medicine and Endocrine and Autonomic Systems, having authored 41 papers that have together received 430 indexed citations. Recurring topics across this work include Obstructive Sleep Apnea Research (15 papers), Acute Myocardial Infarction Research (8 papers), Cardiovascular and Diving-Related Complications (8 papers), Venous Thromboembolism Diagnosis and Management (5 papers), Tracheal and airway disorders (4 papers), Atherosclerosis and Cardiovascular Diseases (4 papers), Atrial Fibrillation Management and Outcomes (4 papers) and Aortic aneurysm repair treatments (4 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (141 citations), Immunology (127 citations), Endocrine and Autonomic Systems (31 citations), Physiology (90 citations) and Pulmonary and Respiratory Medicine (77 citations). Bin Que has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Yingzhong Lin, Qingwei Ji, Shaoping Nie, Hui Ai, Chao Chang, Haiying Hu, Ying Shi, Lei Shi, Zhen Wang and Tao Zeng. Their work appears in journals such as EBioMedicine, American Heart Journal, Journal of the American College of Cardiology, BMJ Open Respiratory Research and Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids.

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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