Raphael Sznitman

137 papers receiving 2.2k citations

Peers

Raphael Sznitman
Comparison fields: 5 of 144
  • Ophthalmology 374
  • Aging 60
  • Radiology, Nuclear Medicine and Imaging 649
  • Health Informatics 42
  • Computer Vision and Pattern Recognition 571
Replace María J. Ledesma‐Carbayo with:
María J. Ledesma‐Carbayo Spain
A. Santos Spain
Hideo Yokota Japan
Vicente Grau United Kingdom
Mathews Jacob United States
Andy Tsai United States
Amir A. Amini United States
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Caroline Essert France
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Citations per year

Countries citing papers authored by Raphael Sznitman

Since Specialization
Citations

This map shows the geographic impact of Raphael Sznitman'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 Sznitman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raphael Sznitman more than expected).

Fields of papers citing papers by Raphael Sznitman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Raphael Sznitman. 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 Sznitman. The network helps show where Raphael Sznitman may publish in the future.

Co-authors

The 25 scholars most cited alongside Raphael Sznitman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Raphael Sznitman Line = papers co-authored together Raphael Sznitman links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 145 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018101
2 202275
3 201574
4 201771
5 201871
6 201870
7 201766
8 201063
9 202160
10 202158
11 201256
12 201855
13 201250
14 201150
15 202149
16 201948
17 201248
18 201448
19 201047
20 201945

About Raphael Sznitman

Raphael Sznitman is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Biomedical Engineering, Ophthalmology and Artificial Intelligence, having authored 145 papers that have together received 2.3k indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (27 papers), Optical Coherence Tomography Applications (16 papers), Domain Adaptation and Few-Shot Learning (14 papers), Retinal and Macular Surgery (13 papers), Advanced Image and Video Retrieval Techniques (12 papers), Machine Learning and Algorithms (11 papers), Glaucoma and retinal disorders (10 papers) and Retinal Diseases and Treatments (10 papers). The work is most often cited by research in Ophthalmology (374 citations), Aging (60 citations), Radiology, Nuclear Medicine and Imaging (649 citations), Health Informatics (42 citations) and Computer Vision and Pattern Recognition (571 citations). Raphael Sznitman has collaborated with scholars based in Switzerland, United States and United Kingdom. Frequent co-authors include Pascal Fua, Bruno Jedynak, Gregory D. Hager, Pablo Márquez-Neila, Russell H. Taylor, Rogério Richa, Martin S. Zinkernagel, Thomas Kurmann, Sebastián Wolf and Ksenia Konyushkova. Their work appears in journals such as International Journal of Computer Assisted Radiology and Surgery, Scientific Reports, Translational Vision Science & Technology, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine Intelligence.

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.

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