Raphael Sonabend
Impact in
- Modeling and Simulation top 10%
- COVID-19 epidemiological studies
- Infectious Diseases top 10%
- COVID-19 Clinical Research Studies
- SARS-CoV-2 and COVID-19 Research
Papers in
-
- SARS-CoV-2 and COVID-19 Research 3
- COVID-19 Clinical Research Studies 2
-
- Explainable Artificial Intelligence (XAI) 3
- Co-authors
- Bernd Bischl (5 shared papers)Sebastian J. Vollmer (3 shared papers)Bilal A. Mateen (6 shared papers)Michel Lang (3 shared papers)Andreas Bender (2 shared papers)Spiros Denaxas (2 shared papers)Andrew McGovern (2 shared papers)Andrew T. Hattersley (2 shared papers)
- Journals
- PLoS Computational Biology (2 papers)Bioinformatics (2 papers)Nature Communications (1 paper)Diabetes Care (1 paper)Journal of Anthropological Archaeology (1 paper)
- Partner nations
- United KingdomGermanyAustralia
In The Last Decade
Raphael Sonabend
17 papers receiving 313 citations
Peers
Comparison fields: 5 of 109
- Modeling and Simulation 31
- Infectious Diseases 122
- Archeology 5
- Health Informatics 4
- Health 22
Countries citing papers authored by Raphael Sonabend
This map shows the geographic impact of Raphael Sonabend'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 Raphael Sonabend with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raphael Sonabend more than expected).
Fields of papers citing papers by Raphael Sonabend
This network shows the impact of papers produced by Raphael Sonabend. 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 Raphael Sonabend. The network helps show where Raphael Sonabend may publish in the future.
Co-authors
The 25 scholars most cited alongside Raphael Sonabend, 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 | 120 | |
| 2 | 2021 | 61 | |
| 3 | 2024 | 45 | |
| 4 | 2023 | 18 | |
| 5 | 2023 | 16 | |
| 6 | 2023 | 14 | |
| 7 | 2021 | 10 | |
| 8 | 2021 | 10 | |
| 9 | 2022 | 7 | |
| 10 | 2020 | 5 | |
| 11 | 2020 | 4 | |
| 12 | 2018 | 3 | |
| 13 | 2023 | 2 | |
| 14 | 2018 | 2 | |
| 15 | mlr3proba: Machine Learning Survival Analysis in R. | 2020 | 1 |
| 16 | 2020 | 1 | |
| 17 | 2019 | 1 | |
| 18 | 2024 | 0 | |
| 19 | 2024 | 0 |
About Raphael Sonabend
Raphael Sonabend is a scholar working on Infectious Diseases, Artificial Intelligence, Health, Modeling and Simulation and Molecular Biology, having authored 19 papers that have together received 320 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (4 papers), Explainable Artificial Intelligence (XAI) (3 papers), Vaccine Coverage and Hesitancy (3 papers), SARS-CoV-2 and COVID-19 Research (3 papers), Artificial Intelligence in Healthcare and Education (2 papers), Statistical Methods and Inference (2 papers), COVID-19 Clinical Research Studies (2 papers) and Diabetes and associated disorders (2 papers). The work is most often cited by research in Modeling and Simulation (31 citations), Infectious Diseases (122 citations), Archeology (5 citations), Health Informatics (4 citations) and Health (22 citations). Raphael Sonabend has collaborated with scholars based in United Kingdom, Germany and Australia. Frequent co-authors include Bernd Bischl, Sebastian J. Vollmer, Bilal A. Mateen, Michel Lang, Andreas Bender, Spiros Denaxas, Andrew McGovern, Andrew T. Hattersley, Franz J. Király and John Dennis. Their work appears in journals such as PLoS Computational Biology, Bioinformatics, Nature Communications, Diabetes Care and Journal of Anthropological Archaeology.
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.