Reuben Dorent
- Radiology, Nuclear Medicine and Imaging
- Epidemiology
- Computer Vision and Pattern Recognition top 10%
- Neurology
- Artificial Intelligence
- Co-authors
- Tom VercauterenSébastien OurselinJonathan ShapeyRobert BradfordShakeel R. SaeedSotirios BisdasNeil KitchenIan Paddick
- Topics
- Meningioma and schwannoma management (6 papers)Domain Adaptation and Few-Shot Learning (5 papers)Radiomics and Machine Learning in Medical Imaging (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaScientific ReportsJournal of neurosurgery
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
Reuben Dorent
14 papers receiving 249 citations
Peers
Comparison fields: 5 of 50
- Radiology, Nuclear Medicine and Imaging 97
- Epidemiology 86
- Computer Vision and Pattern Recognition 70
- Neurology 63
- Artificial Intelligence 44
Countries citing papers authored by Reuben Dorent
This map shows the geographic impact of Reuben Dorent'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 Reuben Dorent with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Reuben Dorent more than expected).
Fields of papers citing papers by Reuben Dorent
This network shows the impact of papers produced by Reuben Dorent. 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 Reuben Dorent. The network helps show where Reuben Dorent may publish in the future.
Co-authorship network of co-authors of Reuben Dorent
This figure shows the co-authorship network connecting the top 25 collaborators of Reuben Dorent. A scholar is included among the top collaborators of Reuben Dorent based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Reuben Dorent. Reuben Dorent is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 0 | |
| 7 | 17 | |
| 8 | 2 | |
| 9 | 6 | |
| 10 | 0 | |
| 11 | 0 | |
| 12 | 8 | |
| 13 | 8 | |
| 14 | 48 | |
| 15 | 17 | |
| 16 | 7 | |
| 17 | 1 | |
| 18 | 39 | |
| 19 | 19 | |
| 20 | 75 |
About Reuben Dorent
Reuben Dorent is a scholar working on Computer Vision and Pattern Recognition, Neurology and Genetics, having authored 21 papers that have together received 253 indexed citations. Recurring topics across this work include Meningioma and schwannoma management (6 papers), Domain Adaptation and Few-Shot Learning (5 papers) and Radiomics and Machine Learning in Medical Imaging (4 papers). The work is most often cited by research in Health Informatics (8 citations), Neurology (44 citations) and Radiology, Nuclear Medicine and Imaging (97 citations). Reuben Dorent has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Tom Vercauteren, Sébastien Ourselin, Jonathan Shapey, Robert Bradford, Shakeel R. Saeed, Sotirios Bisdas, Neil Kitchen, Ian Paddick, Guotai Wang and Alexis Dimitriadis. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and Journal of neurosurgery.
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.