William Barcella
Impact in
- Nephrology top 5%
- Parathyroid Disorders and Treatments
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- Cardiomyopathy and Myosin Studies
- Cardiovascular Function and Risk Factors
Papers in
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- Statistical Methods and Inference 4
- Statistical Methods and Bayesian Inference 3
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- Bayesian Methods and Mixture Models 5
- Co-authors
- Maria De Iorio (7 shared papers)James G. Malone-Lee (5 shared papers)Gianluca Baio (3 shared papers)Tushar Kotecha (1 shared paper)Helen Jane Lachmann (1 shared paper)Amna Abdel‐Gadir (1 shared paper)Candida Cristina Quarta (1 shared paper)Marianna Fontana (1 shared paper)
- Journals
- International Urogynecology Journal (2 papers)Circulation (2 papers)Statistics in Medicine (1 paper)Journal of the Royal Statistical Society Series C (Applied Statistics) (1 paper)Biostatistics (1 paper)
- Partner nations
- United KingdomUnited StatesItaly
In The Last Decade
William Barcella
12 papers receiving 704 citations
William Barcella's Hit Papers
Peers
Comparison fields: 5 of 56
- Nephrology 189
- Cardiology and Cardiovascular Medicine 184
- Molecular Biology 474
- Rheumatology 76
- Radiology, Nuclear Medicine and Imaging 91
Countries citing papers authored by William Barcella
This map shows the geographic impact of William Barcella'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 Barcella with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William Barcella more than expected).
Fields of papers citing papers by William Barcella
This network shows the impact of papers produced by William Barcella. 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 Barcella. The network helps show where William Barcella may publish in the future.
Co-authors
The 25 scholars most cited alongside William Barcella, 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 | Prognostic Value of Late Gadolinium Enhancement Cardiovascular Magnetic Resonance in Cardiac Amyloidosis Hit paper breakdown → | 2015 | 471 |
| 2 | 2018 | 147 | |
| 3 | 2018 | 26 | |
| 4 | 2016 | 25 | |
| 5 | 2017 | 19 | |
| 6 | 2015 | 14 | |
| 7 | 2017 | 14 | |
| 8 | 2017 | 5 | |
| 9 | 2016 | 4 | |
| 10 | 2018 | 3 | |
| 11 | 2015 | 2 | |
| 12 | 2015 | 1 | |
| 13 | 2016 | 1 |
About William Barcella
William Barcella is a scholar working on Statistics and Probability, Artificial Intelligence, Nephrology, Political Science and International Relations and Molecular Biology, having authored 13 papers that have together received 732 indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (5 papers), Statistical Methods and Inference (4 papers), Amyloidosis: Diagnosis, Treatment, Outcomes (3 papers), Statistical Methods and Bayesian Inference (3 papers), Middle East and Rwanda Conflicts (1 paper), Parathyroid Disorders and Treatments (1 paper), Terrorism, Counterterrorism, and Political Violence (1 paper) and Jewish and Middle Eastern Studies (1 paper). The work is most often cited by research in Nephrology (189 citations), Cardiology and Cardiovascular Medicine (184 citations), Molecular Biology (474 citations), Rheumatology (76 citations) and Radiology, Nuclear Medicine and Imaging (91 citations). William Barcella has collaborated with scholars based in United Kingdom, United States and Italy. Frequent co-authors include Maria De Iorio, James G. Malone-Lee, Gianluca Baio, Tushar Kotecha, Helen Jane Lachmann, Amna Abdel‐Gadir, Candida Cristina Quarta, Marianna Fontana, James Moon and Heerajnarain Bulluck. Their work appears in journals such as International Urogynecology Journal, Circulation, Statistics in Medicine, Journal of the Royal Statistical Society Series C (Applied Statistics) and Biostatistics.
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.