Ken Cheung
- Applied Psychology top 2%
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- Cardiovascular Health and Disease Prevention 8
- General Health Professions top 2%
- Oncology top 10%
- Genetics top 5%
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- Statistical Methods in Clinical Trials 10
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- Cerebrovascular and Carotid Artery Diseases 10
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- Health Systems, Economic Evaluations, Quality of Life 7
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- Meta-analysis and systematic reviews 7
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- Cardiac Imaging and Diagnostics 5
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- Acute Ischemic Stroke Management 5
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- Nutritional Studies and Diet 3
- Co-authors
- Mitchell S.V. ElkindRalph L. SaccoNaihua DuanC. Hendricks BrownClinton B. WrightYeseon Park MoonStephen M. SchuellerDavid C. Mohr
- Journals
- Stroke (8 papers)Journal of the American Heart Association (3 papers)Cerebrovascular Diseases (3 papers)
- Partner nations
- United StatesUnited KingdomItaly
In The Last Decade
Ken Cheung
56 papers receiving 2.5k citations
Hit Papers
Peers
Comparison fields: 5 of 137
- Applied Psychology 256
- Cardiology and Cardiovascular Medicine 527
- General Health Professions 454
- Oncology 427
- Genetics 162
Countries citing papers authored by Ken Cheung
This map shows the geographic impact of Ken Cheung'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 Ken Cheung with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ken Cheung more than expected).
Fields of papers citing papers by Ken Cheung
This network shows the impact of papers produced by Ken Cheung. 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 Ken Cheung. The network helps show where Ken Cheung may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ken Cheung, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 2 | |
| 2 | 2022 | 8 | |
| 3 | 2022 | 3 | |
| 4 | 2021 | 46 | |
| 5 | 2019 | 3 | |
| 6 | 2019 | 1 | |
| 7 | 2018 | 16 | |
| 8 | 2017 | 6 | |
| 9 | 2017 | 16 | |
| 10 | 2016 | 3 | |
| 11 | 2015 | 22 | |
| 12 | 2015 | 9 | |
| 13 | 2015 | 165 | |
| 14 | 2015 | 33 | |
| 15 | 2015 | 8 | |
| 16 | 2014 | 96 | |
| 17 | 2013 | 130 | |
| 18 | 2013 | 52 | |
| 19 | 2010 | 44 | |
| 20 | 2000 | 7 |
About Ken Cheung
Ken Cheung is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty, Cardiology and Cardiovascular Medicine, Neurology and Applied Psychology, having authored 56 papers that have together received 2.5k indexed citations. Recurring topics across this work include Statistical Methods in Clinical Trials (10 papers), Cerebrovascular and Carotid Artery Diseases (10 papers), Cardiovascular Health and Disease Prevention (8 papers), Health Systems, Economic Evaluations, Quality of Life (7 papers), Meta-analysis and systematic reviews (7 papers), Cardiac Imaging and Diagnostics (5 papers), Acute Ischemic Stroke Management (5 papers) and Nutritional Studies and Diet (3 papers). The work is most often cited by research in Applied Psychology (256 citations), Cardiology and Cardiovascular Medicine (527 citations), General Health Professions (454 citations), Oncology (427 citations) and Genetics (162 citations). Ken Cheung has collaborated with scholars based in United States, United Kingdom and Italy. Frequent co-authors include Mitchell S.V. Elkind, Ralph L. Sacco, Naihua Duan, C. Hendricks Brown, Clinton B. Wright, Yeseon Park Moon, Stephen M. Schueller, David C. Mohr, Tatjana Rundek and Hannah Gardener. Their work appears in journals such as Stroke, Journal of the American Heart Association, Cerebrovascular Diseases, Journal of Clinical Oncology and Neurology.
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.