Jonathan Passerat‐Palmbach
- Artificial Intelligence top 5%
- Radiology, Nuclear Medicine and Imaging top 5%
- Computer Vision and Pattern Recognition top 5%
- Health Informatics top 2%
- Biomedical Engineering
- Co-authors
- Daniel RueckertWenjia BaiOzan OktayMartin RajchlJoseph V. HajnalDmitrii UsyninGeorgios KaissisBernhard Kainz
- Topics
- Functional Brain Connectivity Studies (5 papers)Privacy-Preserving Technologies in Data (4 papers)Algorithms and Data Compression (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE Transactions on Pattern Analysis and Machine IntelligenceNeuroImage
- Partner nations
- United KingdomFranceUnited States
In The Last Decade
Jonathan Passerat‐Palmbach
18 papers receiving 763 citations
Hit Papers
Peers
Comparison fields: 5 of 111
- Artificial Intelligence 365
- Radiology, Nuclear Medicine and Imaging 256
- Computer Vision and Pattern Recognition 233
- Health Informatics 84
- Biomedical Engineering 79
Countries citing papers authored by Jonathan Passerat‐Palmbach
This map shows the geographic impact of Jonathan Passerat‐Palmbach'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 Jonathan Passerat‐Palmbach with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan Passerat‐Palmbach more than expected).
Fields of papers citing papers by Jonathan Passerat‐Palmbach
This network shows the impact of papers produced by Jonathan Passerat‐Palmbach. 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 Jonathan Passerat‐Palmbach. The network helps show where Jonathan Passerat‐Palmbach may publish in the future.
Co-authorship network of co-authors of Jonathan Passerat‐Palmbach
This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan Passerat‐Palmbach. A scholar is included among the top collaborators of Jonathan Passerat‐Palmbach 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 Jonathan Passerat‐Palmbach. Jonathan Passerat‐Palmbach is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | End-to-end privacy preserving deep learning on multi-institutional medical imagingbreakdown → | 255 |
| 2 | 32 | |
| 3 | 7 | |
| 4 | 34 | |
| 5 | 55 | |
| 6 | Fostering the use of methods for geosimulation models sensitivity analysis and validation | 1 |
| 7 | 37 | |
| 8 | 2 | |
| 9 | 9 | |
| 10 | 29 | |
| 11 | 257 | |
| 12 | 1 | |
| 13 | 9 | |
| 14 | 14 | |
| 15 | 2 | |
| 16 | 5 | |
| 17 | 16 | |
| 18 | 8 |
About Jonathan Passerat‐Palmbach
Jonathan Passerat‐Palmbach is a scholar working on Health Informatics, Computer Vision and Pattern Recognition and Cognitive Neuroscience, having authored 18 papers that have together received 773 indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (5 papers), Privacy-Preserving Technologies in Data (4 papers) and Algorithms and Data Compression (4 papers). The work is most often cited by research in Health Informatics (84 citations), Computer Vision and Pattern Recognition (233 citations) and Artificial Intelligence (365 citations). Jonathan Passerat‐Palmbach has collaborated with scholars based in United Kingdom, France and United States. Frequent co-authors include Daniel Rueckert, Wenjia Bai, Ozan Oktay, Martin Rajchl, Joseph V. Hajnal, Dmitrii Usynin, Georgios Kaissis, Bernhard Kainz, Mellisa Damodaram and Konstantinos Kamnitsas. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and NeuroImage.
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.