Raphaël Veil
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
Papers in
-
- Artificial Intelligence in Healthcare and Education 3
-
- Olfactory and Sensory Function Studies 1
- Co-authors
- C. Adamsbaum (2 shared papers)Alexandra Rouquette (2 shared papers)Ivan Lerner (1 shared paper)Anne‐Sophie Jannot (2 shared papers)Brigitte Ranque (2 shared papers)Jérome Nevoux (1 shared paper)Isabelle Poizot‐Martin (1 shared paper)Pierre Delobel (1 shared paper)
- Journals
- Diagnostic and Interventional Imaging (2 papers)BMC Medical Education (1 paper)Liver International (1 paper)Genetic Epidemiology (1 paper)Journal of Clinical Medicine (1 paper)
- Partner nations
- FranceSwitzerlandUnited Kingdom
In The Last Decade
Raphaël Veil
12 papers receiving 319 citations
Peers
Comparison fields: 5 of 32
- Health Informatics 67
- Modeling and Simulation 58
- Infectious Diseases 71
- Virology 2
- Pharmacy 1
Countries citing papers authored by Raphaël Veil
This map shows the geographic impact of Raphaël Veil'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 Raphaël Veil with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raphaël Veil more than expected).
Fields of papers citing papers by Raphaël Veil
This network shows the impact of papers produced by Raphaël Veil. 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 Raphaël Veil. The network helps show where Raphaël Veil may publish in the future.
Co-authors
The 25 scholars most cited alongside Raphaël Veil, 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 | 2020 | 189 | |
| 2 | 2021 | 76 | |
| 3 | 2023 | 16 | |
| 4 | 2018 | 13 | |
| 5 | 2019 | 13 | |
| 6 | 2019 | 10 | |
| 7 | 2023 | 5 | |
| 8 | 2022 | 4 | |
| 9 | 2018 | 2 | |
| 10 | 2019 | 2 | |
| 11 | 2018 | 1 | |
| 12 | 2024 | 1 | |
| 13 | 2022 | 0 | |
| 14 | 2024 | 0 | |
| 15 | 2026 | 0 |
About Raphaël Veil
Raphaël Veil is a scholar working on Health Informatics, Sensory Systems, Genetics, Statistics and Probability and Surgery, having authored 15 papers that have together received 332 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (3 papers), Cystic Fibrosis Research Advances (1 paper), Olfactory and Sensory Function Studies (1 paper), Gene expression and cancer classification (1 paper), Innovations in Medical Education (1 paper), Pediatric Hepatobiliary Diseases and Treatments (1 paper), Surgical Simulation and Training (1 paper) and Hemoglobinopathies and Related Disorders (1 paper). The work is most often cited by research in Health Informatics (67 citations), Modeling and Simulation (58 citations), Infectious Diseases (71 citations), Virology (2 citations) and Pharmacy (1 citation). Raphaël Veil has collaborated with scholars based in France, Switzerland and United Kingdom. Frequent co-authors include C. Adamsbaum, Alexandra Rouquette, Ivan Lerner, Anne‐Sophie Jannot, Brigitte Ranque, Jérome Nevoux, Isabelle Poizot‐Martin, Pierre Delobel, Jean‐François Papon and Charlie Bouthors. Their work appears in journals such as Diagnostic and Interventional Imaging, BMC Medical Education, Liver International, Genetic Epidemiology and Journal of Clinical Medicine.
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.