Quentin Caudron
Impact in
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- Antibiotic Use and Resistance
- Molecular Medicine top 1%
- Antibiotic Resistance in Bacteria
Papers in
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- Anomaly Detection Techniques and Applications 2
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- COVID-19 epidemiological studies 3
- Co-authors
- Bryan T. Grenfell (3 shared papers)Simon A. Levin (1 shared paper)Ashvin Ashok (1 shared paper)Thomas P. Van Boeckel (1 shared paper)Ramanan Laxminarayan (1 shared paper)Sumanth Gandra (1 shared paper)Antoine Nicot (1 shared paper)Sylvain Gandon (1 shared paper)
- Journals
- PLoS Computational Biology (1 paper)Frontiers in Immunology (1 paper)The Lancet Infectious Diseases (1 paper)Multimedia Tools and Applications (1 paper)Journal of The Royal Society Interface (1 paper)
- Partner nations
- United StatesUnited KingdomIndia
In The Last Decade
Quentin Caudron
10 papers receiving 1.8k citations
Quentin Caudron's Hit Papers
Peers
Comparison fields: 5 of 140
- Applied Microbiology and Biotechnology 605
- Molecular Medicine 413
- Pollution 513
- Pharmacology 206
- Clinical Biochemistry 75
Countries citing papers authored by Quentin Caudron
This map shows the geographic impact of Quentin Caudron'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 Quentin Caudron with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Quentin Caudron more than expected).
Fields of papers citing papers by Quentin Caudron
This network shows the impact of papers produced by Quentin Caudron. 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 Quentin Caudron. The network helps show where Quentin Caudron may publish in the future.
Co-authors
The 25 scholars most cited alongside Quentin Caudron, 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 | Global antibiotic consumption 2000 to 2010: an analysis of national pharmaceutical sales data Hit paper breakdown → | 2014 | 1721 |
| 2 | 2018 | 37 | |
| 3 | 2018 | 35 | |
| 4 | 2020 | 21 | |
| 5 | 2024 | 16 | |
| 6 | 2014 | 13 | |
| 7 | 2020 | 11 | |
| 8 | 2023 | 5 | |
| 9 | 2012 | 5 | |
| 10 | 2023 | 4 |
About Quentin Caudron
Quentin Caudron is a scholar working on Artificial Intelligence, Modeling and Simulation, Social Psychology, Computer Vision and Pattern Recognition and Epidemiology, having authored 10 papers that have together received 1.9k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (3 papers), Neuroendocrine regulation and behavior (2 papers), Generative Adversarial Networks and Image Synthesis (2 papers), Anomaly Detection Techniques and Applications (2 papers), Evolution and Genetic Dynamics (2 papers), Digital Media Forensic Detection (2 papers), Antibiotic Use and Resistance (1 paper) and Insect Utilization and Effects (1 paper). The work is most often cited by research in Applied Microbiology and Biotechnology (605 citations), Molecular Medicine (413 citations), Pollution (513 citations), Pharmacology (206 citations) and Clinical Biochemistry (75 citations). Quentin Caudron has collaborated with scholars based in United States, United Kingdom and India. Frequent co-authors include Bryan T. Grenfell, Simon A. Levin, Ashvin Ashok, Thomas P. Van Boeckel, Ramanan Laxminarayan, Sumanth Gandra, Antoine Nicot, Sylvain Gandon, Romain Pigeault and Ana Rivero. Their work appears in journals such as PLoS Computational Biology, Frontiers in Immunology, The Lancet Infectious Diseases, Multimedia Tools and Applications and Journal of The Royal Society Interface.
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.