Ke Wan

1.7k citations
114 papers · 1.0k · h-index 19

Impact in

Papers in

Ke Wan

103 papers receiving 1.0k citations

Peers

Ke Wan
Comparison fields: 5 of 95
  • Cardiology and Cardiovascular Medicine 452
  • Radiology, Nuclear Medicine and Imaging 181
  • Nephrology 34
  • Critical Care and Intensive Care Medicine 16
  • Epidemiology 97
Replace Go Hiasa with:
Go Hiasa Japan
Mikael Kjær Poulsen Denmark
Evgeny Belyavskiy Germany
Jo Mahenthiran United States
Biljana Putniković Serbia
Arcangelo D’Errico Italy
Peder Sörensson Sweden
Raphael Wurm Austria
Melissa A. Daubert United States
Daniel D. Borgeson United States
Ke Wan relative to Go Hiasa Japan Go Hiasa's profile →
Citations per field
00.5×2×4×6×8×9.5×
Go Hiasa · 1×
Citations per year

Countries citing papers authored by Ke Wan

Since Specialization
Citations

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

Fields of papers citing papers by Ke Wan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 114 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201567
2 201850
3 202047
4 201839
5 202037
6 201931
7 202031
8 201729
9 201728
10 202027
11 202027
12 201827
13 202126
14 201926
15 202023
16 201922
17 202321
18 201819
19 202318
20 201417

About Ke Wan

Ke Wan is a scholar working on Cardiology and Cardiovascular Medicine, Molecular Biology, Physiology, Epidemiology and Radiology, Nuclear Medicine and Imaging, having authored 114 papers that have together received 1.0k indexed citations. Recurring topics across this work include Cardiovascular Function and Risk Factors (16 papers), Amyloidosis: Diagnosis, Treatment, Outcomes (13 papers), Cardiomyopathy and Myosin Studies (12 papers), Dementia and Cognitive Impairment Research (8 papers), Cardiac Imaging and Diagnostics (7 papers), Alzheimer's disease research and treatments (5 papers), Cardiac pacing and defibrillation studies (4 papers) and Statistical Methods and Inference (4 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (452 citations), Radiology, Nuclear Medicine and Imaging (181 citations), Nephrology (34 citations), Critical Care and Intensive Care Medicine (16 citations) and Epidemiology (97 citations). Ke Wan has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Yucheng Chen, Yuchi Han, Jiayu Sun, Jie Wang, Yuanwei Xu, Wei Cheng, Weihao Li, Dan Yang, Zhi Zeng and Fuyao Yang. Their work appears in journals such as Journal of Cardiovascular Magnetic Resonance, Journal of Magnetic Resonance Imaging, European Radiology, International Journal of Cardiology 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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