Marc Aerts
Impact in
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- Antibiotic Use and Resistance
- Statistics and Probability top 0.5%
- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
- Advanced Statistical Methods and Models
Papers in
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- Statistical Methods and Bayesian Inference 55
- Statistical Methods and Inference 40
- Statistical Methods in Clinical Trials 27
- Advanced Statistical Methods and Models 16
- Epidemiology 37
- Co-authors
- Victoria Nyawira Nyaga (5 shared papers)Marc Arbyn (5 shared papers)Niel Hens (77 shared papers)Geert Molenberghs (60 shared papers)Pierre Van Damme (31 shared papers)Christel Faes (57 shared papers)Philippe Beutels (36 shared papers)Ziv Shkedy (38 shared papers)
- Journals
- Statistics in Medicine (12 papers)Statistical Modelling (9 papers)Journal of Antimicrobial Chemotherapy (9 papers)Preventive Veterinary Medicine (8 papers)Computational Statistics & Data Analysis (7 papers)
- Partner nations
- BelgiumUnited StatesUganda
In The Last Decade
Marc Aerts
231 papers receiving 6.8k citations
Marc Aerts's Hit Papers
Peers
Comparison fields: 5 of 198
- Applied Microbiology and Biotechnology 354
- Statistics and Probability 952
- Modeling and Simulation 501
- Infectious Diseases 866
- Molecular Medicine 226
Countries citing papers authored by Marc Aerts
This map shows the geographic impact of Marc Aerts'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 Marc Aerts with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marc Aerts more than expected).
Fields of papers citing papers by Marc Aerts
This network shows the impact of papers produced by Marc Aerts. 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 Marc Aerts. The network helps show where Marc Aerts may publish in the future.
Co-authors
The 25 scholars most cited alongside Marc Aerts, 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 241 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Metaprop: a Stata command to perform meta-analysis of binomial data Hit paper breakdown → | 2014 | 1780 |
| 2 | 2011 | 211 | |
| 3 | 2010 | 208 | |
| 4 | 2009 | 170 | |
| 5 | Signs and symptoms for diagnosis of serious infections in children: a prospective study in primary care. | 2007 | 136 |
| 6 | 2011 | 119 | |
| 7 | 2019 | 115 | |
| 8 | 2007 | 104 | |
| 9 | 2006 | 100 | |
| 10 | 2002 | 96 | |
| 11 | 2001 | 88 | |
| 12 | 2009 | 86 | |
| 13 | 2009 | 86 | |
| 14 | 2012 | 86 | |
| 15 | 2009 | 83 | |
| 16 | 2007 | 81 | |
| 17 | 2016 | 78 | |
| 18 | 2000 | 76 | |
| 19 | 2011 | 75 | |
| 20 | 2009 | 71 |
About Marc Aerts
Marc Aerts is a scholar working on Statistics and Probability, Epidemiology, Artificial Intelligence, Food Science and Infectious Diseases, having authored 241 papers that have together received 7.0k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (55 papers), Statistical Methods and Inference (40 papers), Statistical Methods in Clinical Trials (27 papers), COVID-19 epidemiological studies (22 papers), Bayesian Methods and Mixture Models (20 papers), Animal Disease Management and Epidemiology (19 papers), Salmonella and Campylobacter epidemiology (16 papers) and Advanced Statistical Methods and Models (16 papers). The work is most often cited by research in Applied Microbiology and Biotechnology (354 citations), Statistics and Probability (952 citations), Modeling and Simulation (501 citations), Infectious Diseases (866 citations) and Molecular Medicine (226 citations). Marc Aerts has collaborated with scholars based in Belgium, United States and Uganda. Frequent co-authors include Victoria Nyawira Nyaga, Marc Arbyn, Niel Hens, Geert Molenberghs, Pierre Van Damme, Christel Faes, Philippe Beutels, Ziv Shkedy, Gerda Claeskens and Nele Goeyvaerts. Their work appears in journals such as Statistics in Medicine, Statistical Modelling, Journal of Antimicrobial Chemotherapy, Preventive Veterinary Medicine and Computational Statistics & Data Analysis.
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.