Wangde Dai

85 papers receiving 2.0k citations

Peers

Wangde Dai
Comparison fields: 5 of 113
  • Genetics 530
  • Biomaterials 507
  • Cardiology and Cardiovascular Medicine 504
  • Pathology and Forensic Medicine 376
  • Surgery 897
Replace Hiroshi Kamihata with:
Hiroshi Kamihata Japan
Arnfinn Ilebekk Norway
Aaron M. Abarbanell United States
Santosh K. Sanganalmath United States
Marc Hendrikx Belgium
Nicolas Noiseux Canada
Jiunn‐Jye Sheu Taiwan
Fan-Yen Lee Taiwan
Muhammad Ashraf United States
Laura C. Tumiati Canada
Wangde Dai relative to Hiroshi Kamihata Japan Hiroshi Kamihata's profile →
Citations per field
00.5×5.7×
Hiroshi Kamihata · 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 86 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005442
2 2005192
3 2012124
4 2007111
5 201467
6 200667
7 200964
8 201464
9 201755
10 201548
11 200844
12 201230
13 202030
14 201727
15 200926
16 201426
17 200325
18 201325
19 200524
20 201721

About Wangde Dai

Wangde Dai is a scholar working on Cardiology and Cardiovascular Medicine, Pathology and Forensic Medicine, Surgery, Emergency Medicine and Molecular Biology, having authored 86 papers that have together received 2.0k indexed citations. Recurring topics across this work include Cardiac Ischemia and Reperfusion (28 papers), Tissue Engineering and Regenerative Medicine (16 papers), Cardiac Arrest and Resuscitation (15 papers), Electrospun Nanofibers in Biomedical Applications (12 papers), Cardiovascular Function and Risk Factors (12 papers), Mesenchymal stem cell research (11 papers), Cardiovascular Disease and Adiposity (10 papers) and Anesthesia and Neurotoxicity Research (9 papers). The work is most often cited by research in Genetics (530 citations), Biomaterials (507 citations), Cardiology and Cardiovascular Medicine (504 citations), Pathology and Forensic Medicine (376 citations) and Surgery (897 citations). Wangde Dai has collaborated with scholars based in United States, Czechia and India. Frequent co-authors include Robert A. Kloner, Sharon L. Hale, Joan Dow, Loren E. Wold, Bradley J. Martin, Jin-Qiang Kuang, Jianru Shi, Loren E. Wold, Gregory L. Kay and Aarne J. Jyrala. Their work appears in journals such as Journal of Cardiovascular Pharmacology and Therapeutics, Circulation, Journal of the American Heart Association, Scientific Reports and Cardiovascular Drugs and Therapy.

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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