William Yuan
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
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- Marine Invertebrate Physiology and Ecology
Papers in
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- Advanced Causal Inference Techniques 2
- Statistical Methods in Clinical Trials 2
- Statistical Methods and Bayesian Inference 1
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- Health Systems, Economic Evaluations, Quality of Life 2
- Co-authors
- Isaac S. Kohane (5 shared papers)Kun‐Hsing Yu (3 shared papers)Brett K. Beaulieu‐Jones (3 shared papers)Russ B. Altman (1 shared paper)Samuel G. Finlayson (1 shared paper)Vinay Prasad (1 shared paper)Lea Goentoro (1 shared paper)Michael J. Abrams (1 shared paper)
- Journals
- npj Digital Medicine (1 paper)Nature Communications (1 paper)Clinical Pharmacology & Therapeutics (1 paper)Statistics in Medicine (1 paper)International Journal of Obesity (1 paper)
- Partner nations
- United StatesUnited KingdomTaiwan
In The Last Decade
William Yuan
10 papers receiving 297 citations
Peers
Comparison fields: 5 of 103
- Health Informatics 17
- Paleontology 34
- Statistics and Probability 31
- Computational Theory and Mathematics 59
- Family Practice 5
Countries citing papers authored by William Yuan
This map shows the geographic impact of William Yuan'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 William Yuan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William Yuan more than expected).
Fields of papers citing papers by William Yuan
This network shows the impact of papers produced by William Yuan. 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 William Yuan. The network helps show where William Yuan may publish in the future.
Co-authors
The 25 scholars most cited alongside William Yuan, 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 | 2019 | 105 | |
| 2 | 2017 | 62 | |
| 3 | 2015 | 60 | |
| 4 | 2021 | 41 | |
| 5 | 2019 | 14 | |
| 6 | 2024 | 8 | |
| 7 | 2022 | 5 | |
| 8 | 2023 | 4 | |
| 9 | 2021 | 2 | |
| 10 | 2001 | 1 |
About William Yuan
William Yuan is a scholar working on Statistics and Probability, Economics and Econometrics, Statistics, Probability and Uncertainty, Surgery and Molecular Biology, having authored 10 papers that have together received 302 indexed citations. Recurring topics across this work include Health Systems, Economic Evaluations, Quality of Life (2 papers), Meta-analysis and systematic reviews (2 papers), Advanced Causal Inference Techniques (2 papers), Statistical Methods in Clinical Trials (2 papers), Obesity and Health Practices (1 paper), Inflammatory Bowel Disease (1 paper), Statistical Methods and Bayesian Inference (1 paper) and Cephalopods and Marine Biology (1 paper). The work is most often cited by research in Health Informatics (17 citations), Paleontology (34 citations), Statistics and Probability (31 citations), Computational Theory and Mathematics (59 citations) and Family Practice (5 citations). William Yuan has collaborated with scholars based in United States, United Kingdom and Taiwan. Frequent co-authors include Isaac S. Kohane, Kun‐Hsing Yu, Brett K. Beaulieu‐Jones, Russ B. Altman, Samuel G. Finlayson, Vinay Prasad, Lea Goentoro, Michael J. Abrams, Chin‐Lin Guo and Nathan Palmer. Their work appears in journals such as npj Digital Medicine, Nature Communications, Clinical Pharmacology & Therapeutics, Statistics in Medicine and International Journal of Obesity.
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.