Jun Shi

518 citations
43 papers · 368 · h-index 9

Impact in

Papers in

Jun Shi

40 papers receiving 361 citations

Peers

Jun Shi
Comparison fields: 5 of 82
  • Animal Science and Zoology 66
  • Nutrition and Dietetics 84
  • Cardiology and Cardiovascular Medicine 97
  • Pharmacology 39
  • Epidemiology 71
Replace Xiaoyu Zhao with:
Xiaoyu Zhao China
Kimberly W. Black United States
Xiaoling Lv China
Angelo Del Gaudio Italy
Chandra Sekhar Yadavalli United States
Shohei Ogawa Japan
Susan Kaufman Canada
Saray Gutiérrez Sweden
Abdoulaye Diané Canada
Mingming Xue China
Jun Shi relative to Xiaoyu Zhao China Xiaoyu Zhao's profile →
Citations per field
00.5×
Xiaoyu Zhao · 1×
Citations per year

Countries citing papers authored by Jun Shi

Since Specialization
Citations

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

Fields of papers citing papers by Jun Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jun Shi, 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 Jun Shi Line = papers co-authored together Jun Shi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201484
2 201361
3 201735
4 201927
5 202022
6 201720
7 201119
8 202013
9 201812
10 20128
11 20158
12 20226
13 20166
14 20205
15 20154
16 20234
17 20214
18 20203
19 20242
20 20252

About Jun Shi

Jun Shi is a scholar working on Cardiology and Cardiovascular Medicine, Pulmonary and Respiratory Medicine, Epidemiology, Surgery and Oncology, having authored 43 papers that have together received 368 indexed citations. Recurring topics across this work include Cardiac Valve Diseases and Treatments (14 papers), Infective Endocarditis Diagnosis and Management (10 papers), Aortic Disease and Treatment Approaches (10 papers), Cardiac Arrhythmias and Treatments (5 papers), Atrial Fibrillation Management and Outcomes (5 papers), Aortic aneurysm repair treatments (3 papers), Pancreatic and Hepatic Oncology Research (3 papers) and Pancreatitis Pathology and Treatment (2 papers). The work is most often cited by research in Animal Science and Zoology (66 citations), Nutrition and Dietetics (84 citations), Cardiology and Cardiovascular Medicine (97 citations), Pharmacology (39 citations) and Epidemiology (71 citations). Jun Shi has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Kehe Huang, Fei Ren, Xingxiang Chen, Cuiling Pan, Fang Gan, Chaoyi Qin, Yingqiang Guo, Lulu Liu, Hong Zhou and Da Wei Huang. Their work appears in journals such as The Annals of Thoracic Surgery, Therapeutics and Clinical Risk Management, Journal of Materials Chemistry C, ANZ Journal of Surgery and Journal of Agricultural and Food Chemistry.

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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