Dmitrii Usynin
- Artificial Intelligence top 5%
- Health Informatics top 1%
- Radiology, Nuclear Medicine and Imaging
- Computer Vision and Pattern Recognition
- Information Systems
- Co-authors
- Georgios KaissisDaniel RueckertAlexander ZillerMarcus R. MakowskiRickmer BrarenJonathan Passerat‐PalmbachAndrew TraskJason Mancuso
- Topics
- Privacy-Preserving Technologies in Data (8 papers)Adversarial Robustness in Machine Learning (4 papers)Artificial Intelligence in Healthcare and Education (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE Transactions on Pattern Analysis and Machine IntelligenceScientific Reports
- Partner nations
- GermanyUnited KingdomSwitzerland
In The Last Decade
Dmitrii Usynin
8 papers receiving 403 citations
Hit Papers
Peers
Comparison fields: 5 of 74
- Artificial Intelligence 310
- Health Informatics 94
- Radiology, Nuclear Medicine and Imaging 90
- Computer Vision and Pattern Recognition 42
- Information Systems 40
Countries citing papers authored by Dmitrii Usynin
This map shows the geographic impact of Dmitrii Usynin'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 Dmitrii Usynin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dmitrii Usynin more than expected).
Fields of papers citing papers by Dmitrii Usynin
This network shows the impact of papers produced by Dmitrii Usynin. 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 Dmitrii Usynin. The network helps show where Dmitrii Usynin may publish in the future.
Co-authorship network of co-authors of Dmitrii Usynin
This figure shows the co-authorship network connecting the top 25 collaborators of Dmitrii Usynin. A scholar is included among the top collaborators of Dmitrii Usynin 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 Dmitrii Usynin. Dmitrii Usynin 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 | 13 | |
| 3 | 2 | |
| 4 | 15 | |
| 5 | 1 | |
| 6 | End-to-end privacy preserving deep learning on multi-institutional medical imagingbreakdown → | 255 |
| 7 | 87 | |
| 8 | 32 | |
| 9 | 7 |
About Dmitrii Usynin
Dmitrii Usynin is a scholar working on Health Informatics, Artificial Intelligence and Safety Research, having authored 9 papers that have together received 412 indexed citations. Recurring topics across this work include Privacy-Preserving Technologies in Data (8 papers), Adversarial Robustness in Machine Learning (4 papers) and Artificial Intelligence in Healthcare and Education (4 papers). The work is most often cited by research in Health Informatics (94 citations), Artificial Intelligence (310 citations) and Radiology, Nuclear Medicine and Imaging (90 citations). Dmitrii Usynin has collaborated with scholars based in Germany, United Kingdom and Switzerland. Frequent co-authors include Georgios Kaissis, Daniel Rueckert, Alexander Ziller, Marcus R. Makowski, Rickmer Braren, Jonathan Passerat‐Palmbach, Andrew Trask, Jason Mancuso, M. Steinborn and Andreas Saleh. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and Scientific Reports.
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.