Wangde Dai

86 papers receiving 2.1k citations

Peers

Wangde Dai
Comparison fields: 5 of 114
  • Genetics 509
  • Biomaterials 467
  • Surgery 827
  • Cardiology and Cardiovascular Medicine 406
  • Pathology and Forensic Medicine 312
Replace Joan Dow with:
Joan Dow United States
Aaron M. Abarbanell United States
Santosh K. Sanganalmath United States
Oliver Dewald Germany
Hiroshi Kamihata Japan
Nicolas Noiseux Canada
Jiunn‐Jye Sheu Taiwan
Leping Shen United States
Jianan Wang China
Anders Bruun Mathiasen Denmark
Wangde Dai relative to Joan Dow United States Joan Dow's profile →
Citations per field
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Joan Dow · 1×
Citations per year

Countries citing papers authored by Wangde Dai

Since Specialization
Citations

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

Fields of papers citing papers by Wangde Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 93 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005466
2 2005222
3 2012128
4 2007121
5 200673
6 200972
7 201468
8 201467
9 201760
10 201553
11 200846
12 202030
13 201230
14 200328
15 201727
16 201326
17 201426
18 200926
19 200526
20 201422

About Wangde Dai

Wangde Dai is a scholar working on Cardiology and Cardiovascular Medicine, Pathology and Forensic Medicine, Surgery, Genetics and Emergency Medicine, having authored 93 papers that have together received 2.2k indexed citations. Recurring topics across this work include Cardiac Ischemia and Reperfusion (20 papers), Mesenchymal stem cell research (11 papers), Tissue Engineering and Regenerative Medicine (11 papers), Cardiac Arrest and Resuscitation (10 papers), Cardiovascular Disease and Adiposity (9 papers), Cardiovascular Function and Risk Factors (8 papers), Electrospun Nanofibers in Biomedical Applications (7 papers) and Smoking Behavior and Cessation (6 papers). The work is most often cited by research in Genetics (509 citations), Biomaterials (467 citations), Surgery (827 citations), Cardiology and Cardiovascular Medicine (406 citations) and Pathology and Forensic Medicine (312 citations). Wangde Dai has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Robert A. Kloner, Sharon L. Hale, Joan Dow, Bradley J. Martin, Loren E. Wold, Jin-Qiang Kuang, Jianru Shi, Loren E. Wold, Gregory L. Kay and Aarne J. Jyrala. Their work appears in journals such as Circulation, Journal of Cardiovascular Pharmacology and Therapeutics, Journal of the American Heart Association, Cardiovascular Drugs and Therapy and Scientific Reports.

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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