William Wong
Impact in
- Hepatology top 1%
- Hepatitis C virus research
- Hepatocellular Carcinoma Treatment and Prognosis
- Epidemiology top 5%
- Hepatitis B Virus Studies
- Liver Disease Diagnosis and Treatment
- Influenza Virus Research Studies
Papers in
- Hepatology 34
- Hepatitis C virus research 32
- Epidemiology 24
- Hepatitis B Virus Studies 16
- Liver Disease Diagnosis and Treatment 11
- Co-authors
- Murray Krahn (35 shared papers)Jordan J. Feld (25 shared papers)Kelvin Chan (14 shared papers)F. J. Burkowski (3 shared papers)Thomas McFarlane (3 shared papers)Zeny Feng (13 shared papers)Yi Guan (1 shared paper)Connie Y. H. Leung (1 shared paper)
- Journals
- Liver International (6 papers)PharmacoEconomics (5 papers)CMAJ Open (5 papers)PLoS ONE (4 papers)Journal of Viral Hepatitis (4 papers)
- Partner nations
- CanadaUnited StatesIreland
In The Last Decade
William Wong
86 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 111
- Hepatology 481
- Epidemiology 475
- Agronomy and Crop Science 121
- Infectious Diseases 103
- Modeling and Simulation 21
Countries citing papers authored by William Wong
This map shows the geographic impact of William Wong'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 Wong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William Wong more than expected).
Fields of papers citing papers by William Wong
This network shows the impact of papers produced by William Wong. 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 Wong. The network helps show where William Wong may publish in the future.
Co-authors
The 25 scholars most cited alongside William Wong, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 93 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2004 | 147 | |
| 2 | 2018 | 78 | |
| 3 | 2018 | 63 | |
| 4 | 2003 | 60 | |
| 5 | 2015 | 60 | |
| 6 | 2019 | 55 | |
| 7 | 2018 | 47 | |
| 8 | 2011 | 41 | |
| 9 | 2009 | 41 | |
| 10 | 2014 | 36 | |
| 11 | 2017 | 35 | |
| 12 | 2019 | 31 | |
| 13 | 2019 | 29 | |
| 14 | 2017 | 27 | |
| 15 | 2017 | 26 | |
| 16 | 2011 | 24 | |
| 17 | 2019 | 23 | |
| 18 | 2018 | 22 | |
| 19 | 2013 | 21 | |
| 20 | 2019 | 21 |
About William Wong
William Wong is a scholar working on Hepatology, Epidemiology, Oncology, Surgery and Pulmonary and Respiratory Medicine, having authored 93 papers that have together received 1.3k indexed citations. Recurring topics across this work include Hepatitis C virus research (32 papers), Hepatitis B Virus Studies (16 papers), Liver Disease Diagnosis and Treatment (11 papers), Hemophilia Treatment and Research (3 papers), Computational Drug Discovery Methods (3 papers), CAR-T cell therapy research (3 papers), COVID-19 epidemiological studies (2 papers) and Health Systems, Economic Evaluations, Quality of Life (2 papers). The work is most often cited by research in Hepatology (481 citations), Epidemiology (475 citations), Agronomy and Crop Science (121 citations), Infectious Diseases (103 citations) and Modeling and Simulation (21 citations). William Wong has collaborated with scholars based in Canada, United States and Ireland. Frequent co-authors include Murray Krahn, Jordan J. Feld, Kelvin Chan, F. J. Burkowski, Thomas McFarlane, Zeny Feng, Yi Guan, Connie Y. H. Leung, Malik Peiris and T.M. Ellis. Their work appears in journals such as Liver International, PharmacoEconomics, CMAJ Open, PLoS ONE and Journal of Viral Hepatitis.
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.