Tony Vangeneugden
- Virology top 0.5%
- HIV Research and Treatment 19
- Infectious Diseases top 1%
- HIV/AIDS drug development and treatment 27
- HIV/AIDS Research and Interventions 6
- Emergency Medicine top 2%
- Hepatology top 5%
- Hepatitis C virus research 8
- Statistics and Probability top 2%
- Statistical Methods and Bayesian Inference 12
- Statistical Methods in Clinical Trials 9
- Advanced Causal Inference Techniques 6
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- Pharmacological Effects and Toxicity Studies 11
- Co-authors
- Éric LefebvreGeert MolenberghsMartine De PauwSabrina Spinosa‐GuzmanHelena GeysSandra De MeyerAnnouschka LaenenRichard M. W. Hoetelmans
- Partner nations
- BelgiumUnited StatesNetherlands
In The Last Decade
Tony Vangeneugden
56 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 129
- Virology 987
- Infectious Diseases 1.4k
- Emergency Medicine 321
- Hepatology 215
- Statistics and Probability 196
Countries citing papers authored by Tony Vangeneugden
This map shows the geographic impact of Tony Vangeneugden'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 Tony Vangeneugden with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tony Vangeneugden more than expected).
Fields of papers citing papers by Tony Vangeneugden
This network shows the impact of papers produced by Tony Vangeneugden. 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 Tony Vangeneugden. The network helps show where Tony Vangeneugden may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Tony Vangeneugden, 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 | 2021 | 9 | |
| 2 | Marginal correlation in longitudinal binary data based on generalized linear mixed models | 2010 | 1 |
| 3 | 2010 | 6 | |
| 4 | 2010 | 15 | |
| 5 | 2010 | 13 | |
| 6 | 2009 | 46 | |
| 7 | 2008 | 121 | |
| 8 | 2008 | 6 | |
| 9 | 2008 | 30 | |
| 10 | 2008 | 21 | |
| 11 | 2008 | 278 | |
| 12 | 2007 | 17 | |
| 13 | 2007 | 9 | |
| 14 | 2007 | 17 | |
| 15 | 2007 | 72 | |
| 16 | Body mass change and anthropometric-related adverse events at week 24 in treatment-experienced HIV-infected patients receiving TMC114/r or control PIs in POWER 1, 2 and 3 | 2006 | 1 |
| 17 | 2005 | 93 | |
| 18 | 2004 | 60 | |
| 19 | 2002 | 42 | |
| 20 | 1998 | 42 |
About Tony Vangeneugden
Tony Vangeneugden is a scholar working on Virology, Statistics and Probability and Infectious Diseases, having authored 56 papers that have together received 2.0k indexed citations. Recurring topics across this work include HIV/AIDS drug development and treatment (27 papers), HIV Research and Treatment (19 papers), Statistical Methods and Bayesian Inference (12 papers), Pharmacological Effects and Toxicity Studies (11 papers), Statistical Methods in Clinical Trials (9 papers), Hepatitis C virus research (8 papers), HIV/AIDS Research and Interventions (6 papers) and Advanced Causal Inference Techniques (6 papers). The work is most often cited by research in Virology (987 citations), Infectious Diseases (1.4k citations) and Emergency Medicine (321 citations). Tony Vangeneugden has collaborated with scholars based in Belgium, United States and Netherlands. Frequent co-authors include Éric Lefebvre, Geert Molenberghs, Martine De Pauw, Sabrina Spinosa‐Guzman, Helena Geys, Sandra De Meyer, Annouschka Laenen, Richard M. W. Hoetelmans, Els De Paepe and Vanitha Sekar. Their work appears in journals such as The Lancet, Neurology and Biometrics.
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.